As a Staff Data Scientist, you will lead innovation in experimentation and causal inference, helping shape the future of decision-making and product innovation at SIE. You will drive innovative research in experimentation methodologies while mentoring other team members. You’ll be responsible for elevating our experimentation strategy, fostering a culture of curiosity and rigor, and helping cross-functional teams deliver player-first experiences through strong evidence-based decisions.

What You’ll Be Doing:

• Drive innovation in experimentation research by shaping measurement frameworks and best practices, and by developing new methodologies that enhance the quality, speed, and scalability of experiments.
• Advance experimentation infrastructure and tooling, incorporating statistical and machine learning methods to refine analytical capabilities.
• Mentor and guide less-senior data scientists, building expertise in experimentation and causal inference while providing technical direction to ensure rigor and impact.
• Partner with product managers and business leaders to identify high-impact experimentation opportunities and align them with PlayStation’s strategic goals.
• Act as a thought leader in experimentation and causal inference, evangelizing best practices and fostering learning across teams.
• Contribute to research and prototyping of novel experimentation techniques that address complex real-world challenges, such as user behavior variability and data limitations.
• Champion a data-driven culture by establishing experimentation standards, ethical practices, and reproducibility
• Represent the team’s insights and innovations across the broader data science and product communities within PlayStation.
• Stay at the forefront of the field by monitoring emerging developments in experimentation, causal inference, and applied machine learning to continuously evolve capabilities.

What We’re Looking For:

• Master’s Degree or equivalent experience in Applied Math, Economics, Statistics, Computer Science, or related field. Ph.D. or equivalent experience preferred.
• Strong familiarity with the gaming industry and contemporary gaming experiences.
• 8+ years of experience in data science, including extensive hands-on work in experimentation, with at least 2+ years in a mentoring or technical leadership capacity.
• Proven track record of leading experimentation innovation and scaling frameworks within a dynamic business environment.
• Proficiency in SQL and statistical programming languages (e.g., R or Python), especially for causal inference, experimental analysis, and scalable modeling.
• Expertise in causal inference techniques and designing both randomized and quasi-experiments.
• Demonstrated ability to collaborate cross-functionally and influence data strategies that inform business and product decisions.
• Excellent communication and storytelling skills, especially in conveying complex concepts to non-technical stakeholders.
• Experience working with modern data engineering and visualization tools (e.g., Airflow, Git, Tableau, MicroStrategy).
• A strong sense of ownership and an inclusive leadership style that encourages collaboration and innovation.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.

Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. 

Role Overview:

Our Data Science Analytics and Enablement (DSAE) team inspires PlayStation to make impactful, customer-centric decisions through seamless integration of data.

Currently there are over 100 people in the global DSAE team, including data science, data governance and analytics professionals. We work closely with engineering and product management teams to deliver data products, insight, predictive analytics, and data visualisation.

Data Scientists in the DSAE team apply sophisticated analytical methods and tools to drive value from the data through methods such as customer segmentation, predictive modelling, forecasting and other algorithms. Our work delivers an in-depth understanding of consumer behaviours and supports multi-channel targeting and personalisation.

We’re seeking a motivated and collaborative Data Scientist to join our CLV & Next Best Action / Personalisation team, which builds models that help PlayStation understand and influence the value, growth, and engagement of our global player base.

By connecting player behaviours to long-term outcomes, our work creates the intelligence that underpins Customer Lifetime Value (CLV) modelling and guides PlayStation’s Next Best Action and Personalisation strategies. You’ll help shape how PlayStation invests in, retains, and delights its players - and advance our use of modern machine learning at global scale.

This is an exciting opportunity to develop your skills in modern machine learning while contributing to high-impact projects that directly influence how PlayStation engages and retains its players.

What You’ll Be Doing:

• Build and validate models for use cases such as churn prediction, purchase propensity, CLV modelling, and personalised engagement.
• Work with sequential and behavioural data, applying machine learning approaches (e.g., gradient boosting, embeddings, sequence models) to capture player behaviour and growth.
• Partner with commercial, finance, and lifecycle teams to translate business needs into modelling hypotheses that inform engagement strategies.
• Collaborate with analytics and engineering colleagues to ensure models are efficient, robust, and scalable.
• Communicate findings clearly to both technical and non-technical partners, ensuring insights drive measurable outcomes.
• Grow your expertise in modern ML approaches (transformers, representation learning, sequence-to-sequence modelling) through high-visibility projects.

What we're looking for:

You’re curious, analytical, and eager to grow your skills in a commercial data science environment. You bring strong fundamentals in modelling and data manipulation, and you’re motivated by the challenge of applying these to impactful business problems.

• Strong analytical and critical thinking skills, with a passion for understanding customer behaviour and enabling data-driven growth.
• Practical experience with predictive modelling, such as churn, propensity, segmentation, or value modelling.
• Proficiency in Python and SQL, with fluency in common data science libraries.
• Ability to work with large datasets to uncover actionable insights that influence marketing, engagement, or retention strategies.
• Interest or early experience in deep learning approaches — such as transformers, embeddings, or sequence models — with motivation to learn and apply them.
• A collaborative attitude, with the ability to work in cross-functional teams.
• A strong academic background (typically with a Master’s in a technical or mathematical field) or equivalent professional experience.

Nice to Have:

• Experience with A/B testing or experimentation frameworks.
• Familiarity with workflow orchestration tools (e.g., Airflow), feature stores, or visualisation platforms (e.g., Tableau, Domo).
• Exposure to gaming, e-commerce, or subscription-based business models.
• Proven experience of analysing and modelling with “big data” technologies.
• A personal interest in gaming and entertainment.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.

Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. 

Analyst, Commercial Insights – Services 

London, UK (Collab)

Role Overview 

PlayStation is looking for an innovative, detail-oriented, highly motivated Analyst to join our PlayStation Services team. Services sits within the Global Sales and Business Operations organization that manages the PlayStation Plus subscription business, a key revenue generator and innovator for Sony Interactive Entertainment. This role sits within the Planning and Insights team responsible for leading analytics operational excellence in commercial performance, planning, and strategy.  

This role is responsible for insightful and actionable analytics support of our subscription services from a commercial planning standpoint. You will play a critical role in creating data reporting tools, developing methodologies for measuring and forecasting impact to subscriptions, and delivering analytical insights on the performance of offers & promotions, pricing and experience optimizations.  The work you do will directly impact decisions made about the offers and experience made available to PlayStation Plus members. Effective verbal and written communication skills are extremely important, as s/he will collaborate with key stakeholders across a global organization.  

What you will be doing 

• Support the Services Insights team with analysis of commercial and engagement trends across the PlayStation Plus user base, using these insights to inform strategic decisions and improve performance measurability 

• Working across our Commercial, Engagement & Experience and CRO teams, you will be responsible for exploring our subscriptions data for novel insights, deconstructing complex datasets to help improve knowledge of our users 

• Creating recursive frameworks for long term monitoring of business initiatives, helping to identify opportunities for growth and reduce reporting cycle time 

• Working with our Engineering and Reporting teams to democratise insights into actionable outputs 

• Support efforts to optimise our business with experimentation and A/B testing 

• Partner closely with stakeholders within GSBO and other supporting teams to understand and deliver business insights using data 

• Collaborate with data teams across SIE to understand and utilise available tools and resources while contributing learnings and business area expertise to the organization  

What we are looking for 

• Bachelors Degree in a quantitative or computational field or equivalent

• 5+ years experience in analytics related roles 

• Proficient at translating ambiguous business requirements into meaningful analytical insights from start to finish  

• Skilled with SQL, Python and spreadsheet applications (Excel, Google sheets). 

• Knowledge of statistical concepts, subscription metrics and A/B testing 

• Keen attention to detail and ability to deliver high quality analytical work 

• Proven experience creating data visualizations and reports to surface actionable insights  

• Excellent communication skills (written and verbal) 

• Ability to work collaboratively with stakeholders across different teams and levels 

• Strong project management, multi-tasking and organizational skills 

• Ability to adapt quickly in a dynamic, changing, fast-paced business environment 

• Ability to work varying hours as well as a flexible approach to working hours to support global business operations 

Preferred Qualifications 

• Strong technical proficiencies with SQL, Python, Airflow 

• Skilled with visualization tools like Domo, Power BI, Tableau 

• Interest in the gaming industry 

• Knowledge of digital gaming landscape, key players, and competitive offerings 

• Prior experience with subscription businesses preferred 

As a Data Science Manager, you will lead both people and innovation in experimentation and causal inference, helping shape the future of decision-making and product innovation at SIE. This is a hands-on leadership role blending technical depth with managerial responsibilities. You will drive cutting-edge research in experimentation methodologies while mentoring and guiding a team of data scientists. You’ll be responsible for elevating our experimentation strategy, fostering a culture of curiosity and rigor, and helping cross-functional teams deliver player-first experiences through strong evidence-based decisions.

What You’ll Be Doing:

• Lead a team of data scientists focused on experimentation and causal inference; provide technical direction, career development, and mentorship.
• Drive innovation in experimentation research by developing and overseeing new methodologies and frameworks that improve the quality, speed, and scalability of experiments.
• Guide the advancement of experimentation infrastructure and tooling, incorporating statistical and machine learning methods to refine analysis capabilities.
• Partner with product managers, game studios, and business leaders to identify high-impact experimentation opportunities and ensure alignment with PlayStation’s strategic goals.
• Act as a thought leader in experimentation and causal inference, evangelizing best practices and fostering learning across teams.
• Contribute directly to research and prototyping of novel experimentation techniques that address complex real-world constraints, such as user behavior variability and data limitations.
• Champion the growth of a data-driven culture by advocating for experimentation standards, ethical practices, and reproducibility.
• Represent the team’s insights, innovations, and impact across the broader data science and product communities within PlayStation.
• Stay abreast of emerging developments in experimentation, causal inference, and applied machine learning to continuously evolve our capabilities.

What We’re Looking For:

• Master’s Degree or equivalent experience in Applied Math, Economics, Statistics, Computer Science, or related field. Ph.D. or equivalent experience preferred.
• Strong familiarity with the gaming industry and contemporary gaming experiences.
• 6+ years of experience in data science, including hands-on work in experimentation, with at least 2+ years in a formal people management or technical leadership role.
• Proven track record of leading experimentation innovation and scaling frameworks within a dynamic business environment.
• Proficiency in SQL and statistical programming languages (e.g., R or Python), especially for causal inference, experimental analysis, and scalable modeling.
• Expertise in causal inference techniques and designing both randomized and quasi-experiments.
• Demonstrated ability to collaborate cross-functionally and influence data strategies that inform business and product decisions.
• Excellent communication and storytelling skills, especially in conveying complex concepts to non-technical stakeholders.
• Experience working with modern data engineering and visualization tools (e.g., Airflow, Git, Tableau, MicroStrategy).
• A strong sense of ownership and an inclusive leadership style that encourages collaboration and innovation.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

Your future role within QRT

• Your core objective will be to collaborate with Researchers and Analyst to onboard data sources and signals through a centralized framework.
• You will contribute to the design and maintenance of datasets used for signal generation in trading strategies.
• You will also help develop robust data quality checks to enhance monitoring and ensure the longevity of data sources.
• Additionally, you will be responsible for integrating alternative datasets and building tools to automate data pipelines for faster and more reliable delivery.
• Finally, you will provide support to end users, including Quant Researchers and Traders.

Your present skillset

• 2+ years’ hands-on experience in data engineering
• Excellent communication skills and a collaborative mindset to work effectively with other engineers, quants and traders
• Strong software engineering fundamentals and proficiency in Python
• Experience with workflow orchestration frameworks (e.g. Argo, Airflow)
• Experience designing and implementing RESTful APIs and internal service integrations
• Experience with observability tools (e.g. Grafana, CloudWatch)
• Familiarity with Kubernetes, container orchestration, and cloud infrastructure (AWS preferred)
• Exposure to the front-end, particularly with regards to custom monitoring dashboards, is a plus
• Self-starter mentality with the ability to work autonomously within a globally distributed team

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT's collaborative mindset which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

The Treasury function is the financing backbone of QRT, managing the firm’s funding, collateral, margin, cash balances, and counterparty relationships across geographies and asset classes. The Treasury Analytics team builds the data infrastructure and tooling that gives the desk visibility into financing costs, margin requirements, and cash movements. The systems we build direct inform how the firm deploys its capital.

Join our Treasury Analytics team in London as a Data Engineer, supporting and evolving the data infrastructure that powers Treasury's analytics platform, enabling the desk to analyse and optimise how the firm finances its positions in real time.

Role responsibilities

• Design, build and maintain data pipelines to ingest, transform, and serve Treasury data across multiple sources and analytics systems
• Develop and maintain analytical tools to optimise margin, collateral, cash balances, and financing positions across counterparties
• Build the datasets and APIs that power Treasury's analytics platform, enabling the desk to optimise financing costs, monitor counterparty exposure, and manage liquidity in real time
• Evolve the infrastructure as the desk grows by onboarding new data sources, adapting to new requirements, and improving performance and reliability over time
• Onboard new storage and modelling layers, leveraging the right frameworks for different workloads
• Collaborate with desk leadership, traders, and engineers to implement robust, maintainable solutions

Required experience and skills

• 3–6 years' experience building high-performance intraday data applications, ideally in financial services
• Strong SQL, Python, and data modelling skills
• Understanding of data storage formats and trade-offs
• Experience with query optimisation and performance tuning
• Experience with modern orchestration frameworks (e.g. Airflow), cloud platforms, backend web services and networking protocols
• Knowledge of streaming systems and real-time data applications a plus
• Strong technical communication skills and ability to work effectively with a variety of stakeholders

Location

London

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology- and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors.

You will join a Network Engineering team responsible for designing and operating large-scale datacentre and high-performance computing (HPC) network infrastructure. The team works closely with Quantitative Researchers, Traders, and infrastructure teams to ensure reliable, high-performance connectivity across compute and storage platforms.

Your Future Role within QRT
You will:

• Architect, engineer and deliver large-scale datacentre network infrastructure supporting HPC environments
• Design and build network fabrics with a focus on scalability, resilience and performance
• Support connectivity across compute, storage and cloud platforms
• Troubleshoot complex issues across large-scale network environments
• Collaborate with project management and engineering teams across the organisation
• Engage with network vendors and contribute to engineering discussions on products and solutions
• Contribute to a software-driven network engineering approach, including automation and tooling
• Stay informed on industry trends and emerging technologies to evolve network infrastructure

Your present skillset

• Demonstrate expert knowledge of datacentre networking technologies, including EVPN/VXLAN

• Demonstrate expert knowledge of routing protocols and resilient fabric design, with proven experience designing, building and troubleshooting large-scale datacentre network fabrics
• Understand switch ASICs, buffering models, platform capabilities and performance trade-offs
• Have experience with RDMA, RoCE and/or UEC networks
• Understand datacentre physical standards, including fibre, optics, cabling, switch airflow, cooling and power
• Have knowledge of WAN engineering and cloud interconnects supporting hybrid infrastructure and cloud bursting
• Have at least basic practical knowledge of Python or Go/Golang, Ansible, Git and AI-assisted engineering tools such as Claude
• Be comfortable getting hands-on with smaller engineering tasks as well as larger strategic projects
• Be a highly collaborative team player who takes ownership of complex problems and major project deliverables, communicating clearly and working across teams to drive successful outcomes

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Analytics Engineer 

About the Role

We’re looking for an experienced Analytics Engineer to help build the next generation of Contentful’s analytics foundation, powering Insight 360, our unified Snowflake-based data platform.

In this role, you’ll design and maintain robust, scalable data models that make our business data accessible and actionable across all teams. You’ll collaborate with engineers, analysts, and business stakeholders to deliver high-quality, trusted datasets that enable data-driven decision-making across the company.

Your work will sit at the heart of Contentful’s data evolution, helping us move to a modern, governed, and insight-led architecture.

Key Responsibilities 

Data Modeling & Transformation

• Design, build, and maintain efficient, scalable analytics models in dbt and Snowflake.
• Transform raw data from diverse domains (product, finance, sales, marketing, operations) into analytics-ready structures.
• Apply best practices in modularity, documentation, and testing to ensure long-term reliability.

Pipeline Ownership

• Take ownership of analytics engineering projects end-to-end: from scoping requirements through implementation and monitoring.
• Develop reusable, maintainable data transformations that enable self-serve analytics in Tableau and other BI tools.

Enablement & Collaboration

• Partner with analysts, data scientists, and business teams to define and deliver trusted data assets.
• Collaborate with data platform engineers to optimize performance, governance, and cost efficiency in Snowflake.
• Contribute to the shared data catalog and drive adoption of best practices across analytics and engineering teams.

What You’ll Need

Required

• Experience: 3+ years in analytics engineering, data engineering, or BI development in a modern data stack environment.
• Data Modeling: Proven expertise with SQL to build modular and well-documented data models in dbt. Understanding of various data modeling techniques.
• Warehouse Experience: Deep knowledge of Snowflake (warehouses, roles, virtual warehouses, performance tuning).
• Collaboration: Strong ability to work cross-functionally with analysts, engineers, and business stakeholders to translate needs into technical solutions.
• Data Ops: Experience applying version control, testing, and observability practices in dbt or similar frameworks.

Preferred

• Visualization: Experience structuring data for BI tools such as Tableau, focusing on scalability and performance.
• Ingestion & Orchestration: Familiarity with Airflow, or similar tools for data ingestion and orchestration.
• Reverse ETL: Working knowledge of tools like Hightouch for operationalizing insights back into business systems (e.g., Salesforce, Gainsight).
• Governance: Understanding of data cataloging, lineage, and documentation using tools like Atlan

What’s in it for you

• Join an ambitious tech company reshaping the way people build digital experiences
• Full-time employees receive Stock Options for the opportunity to share in the success of our company
• Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.
• We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days,  education days, compassion days for loss, and volunteer days
• Time off to care for and focus on your growing family 
• Use your personal annual education budget to improve your skills and grow in your career
• Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties 
• An annual wellbeing stipend to care for your physical, financial, or emotional health
• A monthly communication phone/internet stipend and phone hardware upgrade reimbursement.
• New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best.

About the Opportunity

Contentful is experiencing rapid growth, and we're on the lookout for a driven Senior Platform Engineer to join our Core DataTeam. In this pivotal role, you'll be at the heart of our data operations, collaborating with developers and internal stakeholders to create cutting-edge tools for data customers while maintaining a highly adaptable platform.

What to expect? 

• Software Development
• Lead the design, development, testing, and deployment of scalable and maintainable software solutions for our data platform.
• Collaborate with cross-functional teams to understand requirements and translate them into technical specifications.
• Data Orchestration
• Architect and implement systems for efficient data orchestration, ensuring optimal performance and reliability.
• Work closely with the Platform Engineers to integrate new technologies and tools into the data platform ecosystem.
• Performance Optimization
• Identify and address performance bottlenecks in the data platform, ensuring optimal data processing and access speed.
• Implement monitoring and alerting systems to proactively identify and resolve issues.
• Problem-Solving
• Daily challenges related to data management, performance optimization, and security.
• Responsibility
• Substantial impact on the stability and performance of Contentful's Data Platform.
• Continuous Learning
• Staying updated with emerging technologies and industry trends is encouraged for your professional growth.
• Collaboration
• You'll work closely with a collaborative team of developers and stakeholders to achieve shared goals.
• Supportive Culture
• Contentful cultivates a supportive culture where team members help each other succeed and innovate through collaboration.

Your role as a Senior Software Engineer at Contentful promises dynamic challenges, collaboration, personal growth, and a supportive team environment. Join us for an exciting journey!

What you need to be successful?

• You have 5+ years of Engineering experience
• You have proficiency in cloud technologies (AWS preferred)
• You have proficient coding skills in Python, (Golang & TypeScript are a plus)
• You are proficient with Infrastructure as Code, Terraform (Terragrunt is a plus)
• You are proficient in CI/CD tools, setting up complex workflows with a focus on CircleCI 
• You have knowledge of Kubernetes & Docker & Helm
• You are experienced with Git
• You have experience with streaming services
• Desirable skills: You are familiar with Apache Airflow and/ or AWS Redshift

You possess strong skills in communication, problem-solving, collaboration, diversity appreciation, and full professional English proficiency, enabling effective and inclusive interactions in diverse contexts.

If you believe we're a good fit but don't meet all the points, please reach out to us. We value diverse perspectives and welcome your unique skills and experiences. Let's explore the possibilities together.

What’s in it for you?

• Join an ambitious tech company reshaping the way people build digital experiences
• Full-time employees receive Stock Options for the opportunity to share in the success of our company
• Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.
• We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days,  education days, compassion days for loss, and volunteer days
• Time off to care for and focus on your growing family 
• Use your personal annual education budget to improve your skills and grow in your career
• Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties 
• An annual wellbeing stipend to care for your physical, financial, or emotional health
• A monthly communication phone/internet stipend and phone hardware upgrade reimbursement.
• New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best.

As part of the Data Infrastructure team you will be supporting mission critical big data platforms, to ensure they are fully performant, reliable, available and secure. We call it data infrastructure engineering, also known as DataOps or Database Administration or SRE.

The role is a mixture of development of tooling and operational support for our platforms, two aspects that go hand-in-hand. It requires attention to detail and curiousity about how the systems work under the hood, and gives you a wide base of skills from low level system tuning to general coding. 

We manage four main storage platforms, namely:

• Apache Solr (~2.2 PB)
• Apache HBase (~450 TB)
• PostgreSQL (~15 TB)
• Kafka (~60 TB)

These platforms are all open source, written in Java, Scala or C, and we maintain in-house builds and patching of them. We use a variety of open-source and in-house developed tooling to manage these services, mostly written in Rust and Python, which run primarily on hundreds of servers in multiple data centres and in the cloud.

We maintain a balance between project work and operational/ad-hoc work for all members in the team, whether they are senior or recent graduates, and your day-to-day work will be a mix of these.

The exact project work will depend on your experience, but we will scope it out collectively to ensure it is both achievable and delivers benefit. Some example projects given to recent graduates are:

• Coding mapreduce jobs to validate data between two multi-TB+ hbase clusters (to run in hours rather than months)
• Building out a python code stack to transparently migrate production clients between clusters (without losing any data or requiring any downtime)
• Building and testing new HBase builds and deploying them live (without putting everyone in Brandwatch out of a job)
• Creating a platform for rolling out our data management systems using Apache Airflow (to stop people re-writing custom job management systems)
• Rolling out a DR solution for hadoop on AWS (while keeping the system performant and not bankrupting the company)

If you're joining the team as a graduate engineer we'll be focusing on developing your knowledge of the storage platforms, how to program against them and how to troubleshoot issues. The aim is that you'd be able to help with the staging support by 3-6 months, and join the rest of the team supporting the production systems in 12 months. You'll also be expected to take a full part in the life of the team and, as your experience grows, start designing the infrastructure we run.

This role is based in Brighton, UK, but working remotely will be possible once the initial 6-12 months of training is complete.

Who we are looking for

In house training for the storage systems and our tooling is a necessary part of this role, but we are looking for someone with a keen interest in large scale storage infrastructure.A successful candidate will be expected to have the following:

• An interest in how computer infrastructure actually works, and a passion for learning
• Interest, and ideally production experience, running storage systems, eg. as part of a selfhosted service, a home lab or as part of academic studies
• Experience with Linux systems administration, including experience of trouble shooting
• Fluency with one or more scripting languages, ideally Bash or Python
• Experience helping your peers
• Pride in the quality of your work
• Experience with any of the following will be beneficial:
  • Development experience, in Python, Java, Rust, C/C++ or Golang.
  • Upstream open-source contributions
  • Academic research in scalability, distributed systems or storage infrastructure
  • Kubernetes experience, ideally running or writing Operators Experience with Docker and with CI/CD pipelines

Soho, London

Hybrid working: 3 days in the office Tues - Thurs

The Role

We are seeking a Data Engineer to join our Data Team, playing a vital part in building the complex, scalable systems that power our data strategy. You will be at the heart of architectural discussions, influencing system design and delivering the high-quality data solutions that bring millions of fans closer to the sports they love. This is a fantastic opportunity to tackle the challenge of optimising our data platforms for real-time AI/ML workloads, mentor talented junior engineers, and make a significant impact on our business. 

At LiveScore Group, we’re the proud home of three of the most exciting brands in the sports and gaming world: LiveScore, LiveScore Bet and Virgin Bet. A fully owned and operated ecosystem that converges the two worlds of sports media and sports betting. We’re proud of the high ratings for our commitment to excellence and fueling fan’s passion for sport driving us to the top.

We don’t just lead; we innovate. Our cutting-edge products and immersive experiences set the standard, but it’s our people who truly make the difference. Every day, our team embody our values: adaptability, teamwork, a fan-driven approach, and an ever-curious mindset that fuels our ambition. As we scale and continue to create a culture that allows all employees to thrive, we know we need the most talented people with diverse backgrounds, perspectives and skills. If you’re good at what you do, come and join us. The more inclusive we are, the more amazing experiences we can create for our users.

We know that job descriptions can sometimes seem daunting, and you might not feel you tick every box. But, if you’re passionate about the role and have relevant experience, we want to hear from you! 

Key Responsibilities 

• Contribute significantly to critical system design decisions, helping to architect data solutions that support real-time workloads.
• Partner with cross-functional teams to translate intricate business needs into effective and innovative data solutions.
• Mentor and provide expert technical guidance to junior engineers, fostering a culture of continuous learning and growth.
• Design data systems to solve problems and improve reliability & cost-effectiveness. 
• Develop and maintain robust, secure integrations with core internal systems and critical third-party platforms. 
• Implement advanced monitoring and alerting, to ensure high system reliability and minimal downtime. 

Skills, Knowledge and Experience 

• You have expert-level proficiency in a core programming language like Python, Java, or Scala, with an emphasis on AI/ML data processing.
• You possess experience with cloud data services and technologies, ideally within the GCP ecosystem (e.g., Dataflow, Pub/Sub, BigQuery, Vertex AI).
• Experience with Airflow environment management and Docker 
• You can clearly and concisely explain intricate technical concepts to both technical and non-technical stakeholders.
• You have extensive experience designing and optimising both real-time and large-scale batch data processing frameworks.
• You have a proven ability to deploy and maintain data infrastructure using Infrastructure as Code (IaC) principles with tools like Terraform.
• You can demonstrate the application of data governance, privacy, and security best practices in a regulated environment.
• You are a proactive and curious problem-solver, skilled in anticipating and resolving system inefficiencies.
• You work seamlessly with cross-functional teams, translating complex requirements into robust data solutions.
• You take full responsibility for the quality, reliability, and performance of the data solutions you help create. 

What can we offer? 

• Fridays Off: Say goodbye to Friday meetings and hello to a three-day weekend! This benefit is part of a trial, to be reviewed in 2026
• Company Performance Bonus
• Flexible Working Agreements where applicable
• Private Healthcare Scheme + Employee Enhanced Assistance
• Enhanced Family Leave - Maternity, Shared Parental & Adoption Leave: up to 6 months at full pay and 6 months at half pay. Paternity leave: up to 4 weeks at full pay
• Subsidised Gym Membership
• Annual Travel Card Loan & Ride to Work Scheme
• Life Assurance (x3 salary)
• Contributory Pension Plan
• Virgin Family: Giving you access to exclusive Virgin offers and experiences
• Thursday drinks in the office and regular socials

Location: UK or Portugal

Department: Engineering

Employment Type: Permanent

About YLD:

Our goal is to help our clients keep moving forward. We work with them to build the skills and capabilities they need to stay ahead of the competition, and we know our success only happens when they succeed. We’re a team of curious, talented people, and we’re committed to making YLD a place where great people want to work, grow, and stay. We’re a remote-first consultancy specialising in software engineering, product design, and data. Our teams are based across London, Lisbon, and Porto, and we create digital solutions that continue to deliver value long after our work is done.

About the role:

As a Senior Data Engineer, you’ll be part of a client team building innovative products. We expect you to be curious, passionate, driven, and enthusiastic. You’ll be proficient at problem-solving, and crafting scalable, resilient, and fault-tolerant architectures. You’ll be an effective communicator and a team player. You and your team will move in a fast-paced engineering environment, achieving outstanding results and delivering exciting projects.

About you:

A YLD Senior Data Engineer is a highly skilled engineer who spans across data engineering and analytics engineering, and knows where the boundaries sit. You've built pipelines and transformation layers. You've inherited messy data projects and made them good. You have opinions about how data teams should work and the humility to adapt them to context.

You have a real passion for the craft and are an active learner who gets excited by the variety that consultancy brings: different clients, different stacks, different problems.

Your day-to-day responsibilities will look like this:

• Delivering data work on client engagements: pipelines, transformation layers, models, and the infrastructure around them
• Adapting to different client contexts, legacy warehouse migrations, greenfield lakehouses, struggling transformation layers that need rescuing
• Defining and evolving our internal standards for data work: testing, documentation, project structure, code review
• Mentoring and growing data engineers across the company
• Showing up for client team moments (internal speakers, learning sessions, social events) to build strong working relationships.
• Contributing to proposals and helping shape engagements during the sales process
• Representing YLD externally through writing, speaking, and contributing to the wider data community.

You’ll have the following skills and experience:

• SQL as engineering: You write SQL that's reviewable, testable, and performs at scale. You understand query planning, engine quirks, and how materialisation choices affect cost and performance
• Python for data: You write typed, testable Python for pipelines and tooling. You've built and maintained production data systems, not just notebooks
• Data modelling: You've made deliberate choices between dimensional, Data Vault, normalised, and denormalised designs. You can explain those trade-offs in terms of flexibility, query performance, and maintainability
• Transformation architecture: You design transformations that are idempotent, incremental, and dependency-aware. You think in DAGs, not scripts
• Pipeline design: You understand batch, streaming, and micro-batch trade-offs. You consider latency, complexity, cost, and reprocessability. And choose the right approach for the problem
• Data testing: You write tests as code, schema contracts, assertions, and transformation logic. You know what to catch at build time vs. defer to observability
• Data observability: You treat data reliability like site reliability. Measurable indicators, alerting, incident response, and root cause analysis
• CI/CD for data: You version, test, and deploy pipelines like software. Environment promotion, rollback strategies, and infrastructure as code for reproducible environments
• Data governance: You've implemented lineage, cataloguing, sensitive data classification, or access control. Not just built pipelines, but made them auditable and secure
• Cost-conscious: You've optimised warehouse spend, storage strategies, or job efficiency. You treat compute as a resource to manage, not ignore
• Platform fluency: You've worked across the modern stack. Orchestration (Airflow, Dagster), warehouses (Snowflake, BigQuery, Databricks), ingestion (Fivetran, Airbyte, custom), and transformation (dbt, Spark)
• Cross-functional fluency: You translate engineering constraints into business terms and negotiate realistic commitments

You’ll be:

• Self-motivated and proactive
• Comfortable with ambiguity, experimentation, and iteration
• Collaborative by default. You work well in teams and across teams
• Analytical and detail-oriented in your approach to problems
• Comfortable context-switching across clients, stacks, and problem types
• Willing to shape engagements, not just deliver them: contributing to proposals, scoping, and client relationships
• Active in the wider data community: writing, speaking, or open-source contribution
• Genuinely committed to diversity, equity, and inclusion

Benefits you'll get:

• Company Private Health care
• Enhanced fully paid maternity and paternity leave for up to 6 months
• Company’s Pension Scheme (UK Only)
• 25 days annual holiday (excluding Public Holidays)
• £2000/€2000 annual allowance for Training/Conferences
• £300/€300 annual allowance for additional hardware
• Wellbeing & Performance Support via Oli including Therapy and Coaching
• Discretionary Bonus (depending on Company performance and results)
• Company laptop
• Generous referral schemes

Our typical Recruitment Process looks like this:

• 1st Interview with someone from the Talent team (30-45 Minutes)
• Technical Interview with our Senior Developers (90 Minutes)
• Call with the Head of Engineering (60 Minutes)

Get a glimpse of what it's like working at YLD! 🤳

Check out our LinkedIn page

We live and breathe our values, and know you will too:

• Growing every day
• Including everyone
• Relationships built on honesty and ethics
• Inspiring solutions
• Winning together

We’re an equal-opportunity employer and value diversity in all its forms. We do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, pregnancy or maternity, age, marital status, or disability. We also offer a remote-first working environment, with flexible working and work–life balance as standard for all employees.

Role Title: Data & AI Intern 

Location of internship: 1 Angel Court, London EC2R 7HJ

Length of Internship: 8 weeks

Start Date: 15th June - 7th August 2026

Schedule/Hours: Monday to Friday, 9:00 - 17:00

Student Type: Penultimate or Final Year students

This role is particularly suited for students studying: Data Science, Computer Science, Business Analytics, Information Systems, Mathematics, Engineering, Economics, or related subjects at undergraduate or postgraduate level

About the Role: 

This internship is designed to give early-career talent structured exposure to how Data and AI supports the bank's priorities. The work focuses on data quality, governance, operational resilience, dashboards, reporting, and safe AI enablement. It suits a student who enjoys both technical learning and understanding how data supports business decisions.

Main duties & responsibilities:

• Learn how Data and AI supports the bank's priorities and wider business outcomes.
• Build or extend a simple data dashboard.
• Review selected Airflow and data warehouse pipelines to understand how data moves through the organisation.
• Use a simple data and governance checklist to assess areas such as ownership, alerting, and naming clarity.
• Take part in a small data and AI governance exercise.
• Build low-code AI agents using templates in a safe, structured environment.
• Present back to the team what you have learned and what opportunities you have identified.

Students will gain: 

• Exposure to real Data and AI work in a banking environment.
• Better understanding of data quality, governance, and operational resilience.
• Experience with dashboards, pipelines, and data storytelling.
• Introductory experience with safe AI enablement and agent-building.
• Better understanding of ownership, controls, and practical business use cases.
• Experience communicating technical and business insights clearly.

Person specification:

• Strong analytical and problem-solving skills.
• Confidence working with data in Excel, SQL, Python, BI tools, or similar.
• Interest in data flows, dashboards, reporting, or AI tools.
• Ability to understand structured processes and translate findings into clear outputs.
• Curiosity and willingness to learn.
• Good communication skills.
• Strong attention to detail.
• Ability to work independently and collaboratively.
• Accountability and openness to feedback.

Nice to have: 

• Familiarity with dashboards, databases, or reporting tools.
• Exposure to Python, SQL, Airflow, cloud tools, or low-code/no-code tools.
• Interest in AI governance, data governance, or operational resilience.
• Ability to bridge technical and business thinking.

Winton leverages quantitative analysis and cutting-edge technology to identify and capitalize on opportunities across global financial markets. We foster a collaborative and intellectually stimulating environment, bringing together individuals with Mathematics, Physics and Computer Science backgrounds who are passionate about applying rigorous scientific methods to financial challenges. As a fundamentally data-driven business, our success is heavily linked to the acquisition, processing, and analysis of vast datasets. High-quality, well-managed data forms the critical foundation for our quantitative research, strategy development, and automated trading systems.
 
As a Data Engineer within our Quantitative Platform team, you will play a pivotal role in building and maintaining the data infrastructure that fuels our research and trading strategies. You will be responsible for the end-to-end lifecycle of diverse datasets – including market, fundamental, and alternative sources – ensuring their timely acquisition, rigorous cleaning and validation, efficient storage, and reliable delivery through robust data pipelines. Working closely with quantitative researchers and technologists, you will tackle complex challenges in data quality, normalization, and accessibility, ultimately providing the high-fidelity, readily available data essential for developing and executing sophisticated investment models in a fast-paced environment.
 

Your responsibilities will include:

• Evaluating, onboarding, and integrating complex data products from diverse vendors, serving as a key technical liaison to ensure data feeds meet our stringent requirements for research and live trading.
• Designing, implementing, and optimizing robust, production-grade data pipelines to transform raw vendor data into analysis-ready datasets, adhering to software engineering best practices and ensuring seamless consumption by our automated trading systems.
• Engineering and maintaining sophisticated automated validation frameworks to guarantee the accuracy, timeliness, and integrity of all datasets, directly upholding the quality standards essential for the efficacy of our quantitative strategies.
• Providing expert operational support for our data pipelines, rapidly diagnosing and resolving critical issues to ensure the uninterrupted flow of high-availability data powering our daily trading activities.
• Participating actively in team rotations, including on-call schedules, to provide essential coverage and maintain the resilience of our data systems outside of standard business hours.

What we are looking for:

• 1+ years’ experience building ETL/ELT pipelines using Python
• Familiarity with various technologies such as S3, Kafka, Airflow, Iceberg. 
• A commitment to engineering excellence and pragmatic technology solutions.
• A desire to work in an operational role at the heart of a dynamic data-centric enterprise.
• Excellent communication and collaboration skills, and the ability to work in a team.

What would be advantageous:

• Strong understanding of financial markets.
• Proficiency working with large financial datasets from various vendors.
• Experience working with hierarchical reference data models.
• Proven expertise in handling high-throughput, real-time market data streams
• Familiarity with distributed computing frameworks such as Apache Spark
• Operational experience supporting real time system

What You’ll Do:

The Monolith AI Platform Engineering Team at CoreWeave is responsible for building and scaling the data and workflow backbone that powers the world’s most advanced engineering simulation and AI workflows — our ambition is to become the super‑intelligent AI test lab for the engineering industry, helping customers ship science, faster. From high‑throughput data ingestion and feature pipelines to model training and real‑time inference, our platform delivers the performant, reliable, and trustworthy data foundation trusted by the world’s largest engineering companies.

The Staff Data Engineer will own and evolve Monolith’s platform data services and ETL offerings — the data onboarding, preparation, and lineage capabilities that turn fragmented, real‑world engineering data into production‑ready training and inference pipelines. You’ll partner with Product, Engineering, and Customer‑facing teams to deeply understand client data challenges and translate them into scalable, self‑serve data platform features.

About the Role:

We’re seeking a Staff Data Engineer who can own Monolith’s data platform surface end‑to‑end: from offline batch pipelines and large historical backfills to low‑latency, real‑time streaming data flows that power online inference and feedback loops. You’ll define and drive our data architecture, champion data quality and lineage, and decide how customer data moves through Monolith from raw ingestion to governed, observable, and reproducible training sets.

You’ll primarily work with internal teams (Product, Customer Success, Forward‑Deployed Engineers, Software Engineers, Data Scientists), and step in as a domain expert when clients need deeper guidance.

In this role, you will:

• Own Monolith’s Data Platform & ETL Surface
• Lead the architecture and evolution of core data services for ingestion, transformation, validation, and lineage across training and inference workloads.
• Design and maintain end‑to‑end data models and schemas that make complex engineering, simulation, and telemetry data discoverable, reusable, and performant.
• Define standards, contracts, and APIs for how product teams and integrations interact with data services.
• Design & Operate Batch + Streaming Pipelines
• Build and operate batch pipelines for large‑scale historical imports, retraining data sets, and migrations from legacy environments.
• Design and implement streaming pipelines (e.g., using Kafka or similar technologies) for event‑driven or real‑time ingestion and transformation that support online inference, monitoring, and feedback loops.
• Select and integrate off‑the‑shelf, industry‑proven ETL / ELT technologies (e.g., workflow orchestrators, ingestion frameworks, transformation engines) and own their rollout and long‑term operation.
• Champion Data Lineage, Governance & DataOps
• Implement and maintain end‑to‑end data lineage from source systems to derived features and model artifacts, enabling reproducibility, compliance, and faster debugging.
• Establish DataOps practices: CI/CD for pipelines, observability (metrics, logs, traces), and operational runbooks for data incidents.
• Help define data quality and governance standards in partnership with Security, Compliance, and Customer Success, including support for privacy and regulatory needs (e.g., GDPR‑aligned flows and data residency discussions).
• Partner Across Monolith & CoreWeave
• Work with Monolith product and engineering teams (platform, agents, experiments, reliability) to expose data services that unlock new user workflows and AI capabilities.
• Collaborate with CoreWeave infrastructure and AI platform teams to leverage storage, compute, and observability for reliable data flows.
• Serve as a technical escalation point for forward‑deployed and customer‑facing engineers when questions go deeper than their playbooks (e.g., architecture diagrams of data flow, lineage, and governance constraints).

Who You Are:

• Experience & Level
• Typically 8+ years of experience as a Data Engineer / Data Platform Engineer (or similar), including ownership of production data pipelines and architectural decisions.
• Demonstrated Staff‑level impact: leading critical data domains and cross‑team initiatives.
• Data Engineering & Architecture
• Deep experience designing end‑to‑end data architectures that cover ingestion, storage, transformation, serving, and observability.
• Strong, hands‑on experience with both batch and streaming pipelines:
• Batch: scheduled workloads, historical backfills, retraining pipelines.
• Streaming: Kafka or similar event streaming platforms plus real‑time transformation patterns for low‑latency consumption.
• Proficiency with SQL and at least one major analytical database or data warehouse (e.g., PostgreSQL or similar) including schema design and performance tuning
• Proficiency with Spark, Ray or similar distributed data processing frameworks.
• Solid understanding of data modeling (event logs, star schemas, feature tables) in multi‑tenant SaaS or platform contexts.
• Tooling & Ecosystem
• Hands‑on with data orchestration and ETL tooling (e.g., Airflow, dbt, Dagster, Temporal, or equivalents) and able to evaluate and recommend tools that fit our needs.
• Experience integrating and operating off‑the‑shelf data infrastructure (not just bespoke systems), including rollout, migration plans, and ongoing ownership.
• Familiarity with cloud infrastructure and containerization (Docker, Kubernetes, at least one major cloud provider) for deploying and scaling data workloads.
• Data Lineage, Quality & DataOps
• Extensive experience implementing data lineage solutions and using them for debugging, compliance, and auditability.
• Strong background in data quality: validation frameworks, monitoring, and guardrails that prevent bad data from reaching downstream consumers.
• Proficiency with DevOps / DataOps practices: infra‑as‑code, CI/CD for pipelines, runbooks, and participation in on‑call / incident response for data issues.
• Programming, Systems & Communication
• Strong programming skills in Python for building data services, transformations, and platform integrations, with an emphasis on maintainability and tests.
• Comfortable working in service‑oriented architectures, reasoning about data contracts, SLAs, and failure modes across services.
• Clear written and verbal communicator who can:
• Explain data architectures and trade‑offs to internal stakeholders, and
• Occasionally join client conversations as a deep domain expert to answer questions about data flows, security, and governance (e.g., with CIOs, heads of data, or security counterparts), while day‑to‑day client interaction is handled by forward‑deployed teams.

Preferred:

• Experience in ML/AI platforms or MLOps environments where data pipelines feed experimentation, training, and inference workflows at scale.
• Background with time‑series, simulation, or experimental data (e.g., physical test benches, sensors, engineering simulations).
• Familiarity with feature stores, experiment tracking systems, or model registries and their integration with upstream pipelines.
• Experience designing data systems for regulated or safety‑critical domains, including privacy, residency, and retention considerations.

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. If some of this describes you, we’d love to talk:

• Product‑minded – you design data platforms and pipelines that are intuitive to use and unlock real workflows for engineers and customers.
• Systems thinker – you enjoy mapping complex data flows, understanding failure modes, and building robust, observable systems.
• Pragmatic – you balance solid engineering with shipping value quickly, knowing when to invest in abstractions and when to deliver incremental improvements.
• Collaborative owner – you partner well across engineering, product, and customer‑facing teams, and you feel responsible for outcomes, not just code.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper‑growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best‑in‑Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking, and foster an environment that encourages collaboration and innovative solutions to complex problems. As we get set for takeoff, the organization’s growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

What You’ll Do:

The Monolith AI Platform Engineering Team at CoreWeave is responsible for building and scaling the core platform that powers the world’s most advanced engineering simulation and AI workflows. From evolving distributed architecture to enabling the next generation of AI-agentic applications, this team delivers the performant, reliable, and scalable foundation trusted by the world’s largest engineering companies.

About the Role:

We are seeking an Engineering Manager to lead the Monolith AI Platform Team and help us scale this mission-critical platform. This individual will grow and guide a team of engineers as we push the boundaries of simulation technology and AI-agentic applications. As the Manager of this team you would have the opportunity to:

• Drive the culture and tone for how your team keeps score — both in how they support each other and how they enable the rest of Monolith AI.
• Support your people and create opportunities for them to be challenged and grow.
• Develop a customer-centric mindset, perform regular needs analysis and prioritization, create and deliver roadmaps, and maintain a highly available and reliable platform.
• Work directly with other engineering teams to assess needs and guide their implementations and integrations with your team’s platform.
• Implement processes and standards to achieve a highly mature practice of testing, distributed systems orchestration, and platform delivery to guarantee a first-class customer experience.
• Grow, change, invest in your teammates, be invested-in, share your ideas, listen to others, be curious, have fun, and, above all, be yourself.

Who You Are:

• 7+ years of software engineering experience, with at least 3 years primarily focused on Python.
• Demonstrable experience building and/or leading software engineering teams.
• Knowledge of ML engineering principles and practices, especially implementing them within production settings.
• Experience working on data-intensive products, whether high-volume (big data) or high-scale (high-load) systems.
• Experience with cloud infrastructure (particularly AWS, Azure/GCP desirable),  including services such as Athena, Synapse, Spark, or Kubernetes.
• Experience with distributed systems and workflow orchestration (e.g. Temporal, Airflow, Kubeflow, Flyte or similar).
• A bottoms-up leadership philosophy focused on enablement, communication, organisation, and inspiration over task management.

Preferred:

• 2+ years of prior experience managing a software engineering team, including recruitment and retention.
• Experience working on AI-based or ML-powered products in a production environment.
• Distributed computing experience (e.g. Spark, Ray, or similar frameworks).
• Full-stack development experience.
• Experience with containerisation and Kubernetes in production workloads.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• Mentorship Mindset: You love helping people on their journeys to become their best selves, elevating others through knowledge sharing and patient guidance.
• Pragmatic Problem-Solver: You balance perfectionism with shipping, making smart trade-offs between short-term delivery and long-term platform goals.
• Technical Excellence: You remain hands-on enough to engage meaningfully in code reviews and technical decisions, and you care about engineering craft.
• Ownership Mentality: You take full responsibility for outcomes and drive initiatives to completion.
• Customer Obsession: You understand that the platform exists to serve customers, and you develop a customer-centric mindset in everything you build.
• Startup Spirit: You’re excited about the dynamism of a fast-growing company and thrive in environments that reward curiosity, adaptability, and impact.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organisation are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

What You’ll Do:

The Monolith AI Platform Engineering Team at CoreWeave is responsible for building and scaling the data and workflow backbone that powers the world’s most advanced engineering simulation and AI workflows — our ambition is to become the super‑intelligent AI test lab for the engineering industry, helping customers ship science, faster. From high‑throughput data ingestion and feature pipelines to model training and real‑time inference, our platform delivers the performant, reliable, and trustworthy data foundation trusted by the world’s largest engineering companies.

The Senior DataOps Engineer II will own and drive all things data observability and operations across our client estate — building the practices, tooling, and culture that make Monolith’s data flows debuggable, auditable, and safe to evolve. You’ll sit at the intersection of platform engineering, data engineering, and reliability, implementing end‑to‑end lineage and DataOps practices while mentoring data producers and consumers on how to manage data as a first‑class product.

You’ll partner closely with Monolith’s Product, Engineering and forward‑deployed teams, as well as with CoreWeave’s infrastructure and AI platform groups, to turn fragmented, real‑world engineering data into well‑governed, observable, and operationally robust pipelines powering our SaaS platform and client‑specific deployments.

About the Role:

We’re seeking an Senior DataOps Engineer II who can act as the hands‑on owner for Monolith’s data observability and operational surface: from batch and streaming pipelines running on our platform, through to the lineage, quality, and runbooks that keep customer environments healthy.

You’ll define and roll out DataOps practices (CI/CD, infra‑as‑code, data SLOs, incident response) across the Monolith estate, implement end‑to‑end data lineage and observability, and serve as the go‑to mentor for engineering teams and client‑facing colleagues on best‑practice data management.

In this role, you will:

• Own Monolith’s Data Observability & Operations Surface
• Design and implement the end‑to‑end observability stack for data workloads (metrics, logs, traces, and data‑quality signals) across batch and streaming pipelines.
• Define and maintain operational SLOs/SLAs for critical data flows powering training, inference, and analytics, and ensure they are measurable and actionable.
• Build dashboards, alerts, and runbooks that allow engineers and on‑call responders to quickly detect, triage, and remediate data incidents.
• Standardise “golden paths” for how teams instrument pipelines, expose health signals, and respond to data‑related failures.

• Implement Data Lineage, Quality & Governance
• Deploy and maintain end‑to‑end data lineage for key domains — from client sources through transformations to features, models, and downstream analytics  so teams can debug, audit, and reason about change.
• Define and roll out data quality checks (schema, freshness, completeness, distribution, drift) and ensure failures integrate cleanly into alerting and incident workflows.
• Partner with Security, Compliance, and customer‑facing teams to encode data governance requirements (e.g., retention, residency, access controls) into our pipelines and tooling.
• Help shape metadata models and catalog conventions so that producers and consumers can reliably discover, understand, and use shared datasets.

• Enable DataOps Practices Across Teams
• Establish CI/CD patterns for data pipelines and related infrastructure, including testing strategies, promotion workflows, and change‑management guardrails.
• Drive adoption of infra‑as‑code for data infrastructure (e.g., pipeline orchestration, storage, observability components), reducing manual drift across environments.
• Define and continuously improve DataOps processes — incident response, post‑incident review, change review, on‑call rotations — with a focus on learning rather than blame.
• Evaluate and integrate best‑of‑breed DataOps and observability tooling where it accelerates our teams, balancing build vs. buy pragmatically.

• Partner Across Monolith, CoreWeave & Clients
• Work with Monolith platform, data, agent, and reliability teams to expose observability and lineage as shared services and patterns other engineers can build on.
• Collaborate with CoreWeave infrastructure and AI platform teams to leverage underlying storage, compute, networking, and observability in service of robust data flows.
• Serve as a technical escalation point for forward‑deployed and customer‑facing engineers when data issues cross service boundaries or require deeper architectural insight.
• Mentor data producers (product teams, integrations, forward‑deployed engineers) and data consumers (data scientists, analysts, client engineers) on resilient schemas, contracts, and operational practices.

Who You Are:

• Experience & Level
• Typically 5–6+ years of experience in DataOps, Data Engineering, DevOps/SRE for data platforms, or similar roles, including end‑to‑end ownership of production data pipelines and their operations.
• Proven track record of operating at Senior IC scope: leading cross‑team initiatives, introducing new practices/tooling, and improving reliability at the platform level.

• DataOps, Pipelines & Tooling
• Strong hands‑on experience designing, deploying, and operating data pipelines in production (batch and/or streaming), including failure modes, retries, and backfills.
• Practical experience with data orchestration and ETL/ELT tooling (e.g., Airflow, Dagster, dbt, Temporal, or similar) and comfort evaluating and integrating new tools where appropriate.
• Solid SQL and/or Spark skills and experience with at least one major analytical database or warehouse; familiarity with time‑series / telemetry data is a plus.

• Observability, Lineage & Data Quality
• Extensive experience implementing data observability — metrics, logging, tracing, dashboards, and alerting — for data‑centric workloads.
• Hands‑on work with data quality frameworks and/or observability platforms to monitor freshness, completeness, schema changes, and anomalies.
• Experience deploying and using data lineage or metadata/catalog solutions, and applying them to debugging, compliance, and change‑impact analysis.

• Platform, Infrastructure & Automation
• Comfortable working in containerised, cloud‑native environments (Kubernetes plus at least one major cloud provider); experience with GPU‑ or compute‑intensive workloads is a bonus.
• Strong automation mindset: infra‑as‑code, CI/CD, and configuration management for data infrastructure and observability components.
• Proficient in Python for building tooling, pipeline glue, and platform integrations; additional languages are a plus.

• Collaboration, Mentorship & Communication
• Clear communicator who can explain complex data flows and failure modes to both deeply technical and non‑specialist audiences.
• Experience mentoring engineers and data practitioners on better data management, observability, and operational hygiene — through documentation, examples, reviews, and office hours.
• Comfortable working in a fast‑moving, high‑ambiguity environment where we balance rapid iteration with the safety and reliability demanded by enterprise engineering clients.

Preferred:

• Experience in ML/AI platforms or MLOps environments where data pipelines power experimentation, training, and inference at scale.
• Background with test, simulation, or time‑series data (e.g., physical test benches, battery labs, automotive/aerospace R&D).
• Familiarity with feature stores, experiment tracking, or model registries and their interaction with upstream data pipelines.
• Prior work in multi‑tenant SaaS platforms, especially those with strong compliance, observability, and uptime requirements.
• Experience supporting or partnering closely with forward‑deployed / professional services teams in complex customer environments.

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who bring diverse experiences — even if you don’t tick every single box. Here are a few qualities we’ve found compatible with our team. If some of this sounds like you, we’d love to talk:

• Data‑obsessed operator – You care deeply about making data systems observable, predictable, and easy to reason about, not just “working most of the time.”
• Systems thinker – You enjoy mapping complex data flows across services, understanding failure modes, and designing for graceful degradation and rapid recovery.
• Pragmatic – You know when to build the ideal abstraction and when to ship the smallest change that meaningfully reduces risk or toil.
• Collaborative mentor – You get energy from helping other teams level up their data practices, and you can influence without heavy process or authority.
• Owner’s mindset – You feel responsible for the outcomes of the platform as a whole, not just the code you write, and you follow issues across boundaries until they’re truly resolved.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper‑growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best‑in‑Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking, and foster an environment that encourages collaboration and innovative solutions to complex problems. As we get set for takeoff, the organization’s growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

What You’ll Do:

The Monolith AI Engineering Team at CoreWeave is responsible for building and scaling the core platform that powers the world’s most advanced engineering simulation and AI workflows. From evolving distributed architecture to enabling the next generation of agentic applications and physical AI, this team delivers the performant, reliable, and scalable foundation trusted by the world’s largest engineering companies.

About the role:

We’re seeking a Principal Software Engineer to lead the architectural evolution of our platform as we scale to meet growing demand from the world’s largest engineering companies. This is a hands-on technical leadership role where you’ll drive critical architectural initiatives while mentoring our engineering team. You’ll own — in conjunction with the VP of Engineering — the technical vision and execution of our platform’s evolution to a more distributed architecture, making it agentic ready for the next generation of AI applications.

In this role, you will:

• Technical Leadership & Architecture
• Drive the ongoing transition from monolithic to distributed architecture.
• Design and implement architecture to be agentic ready, enabling rapid deployment of AI products and MCP server integrations.
• Own technical decisions balancing immediate business needs with long-term architectural goals.
• Hands-On Development
• Write production-quality Python code for critical platform components.
• Build and optimize distributed compute services.
• Implement reliable workflow orchestration patterns.
• Team Mentorship & Collaboration
• Mentor mid-level developers, elevating the technical capabilities of the entire team.
• Establish engineering best practices and architectural patterns.
• Collaborate with product and business stakeholders to translate requirements into technical solutions.
• Guide technical decision-making and prioritization across the engineering organization.
• Interview and onboard new engineers.

Who You Are:

• 12+ years of software engineering experience with at least 2 years in principal/staff engineering roles.
• Expert-level Python development skills with production experience at scale.
• Deep expertise in distributed systems architecture.
• Strong Kubernetes experience with production workloads.
• Hands-on experience with workflow orchestration tools (Temporal, Airflow, Kubeflow, or similar).
• Cloud platform expertise (AWS required, Azure & GCP beneficial).
• Experience with data processing frameworks (Spark, Athena, Ray, or similar).
• Experience with systems having ML Engineering and MLOps aspects.
• Proven track record of leading architectural transformations in growing companies.
• Excellence in technical communication and stakeholder management.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• Technical Excellence: You write clean, maintainable code and design systems that scale.
• Pragmatic Problem-Solver: You balance perfectionism with shipping, making smart trade-offs between short-term delivery and long-term goals.
• Strong Leadership: You proactively identify problems and drive solutions forward.
• Mentorship Mindset: You elevate others through knowledge sharing and patient guidance.
• Ownership Mentality: You take full responsibility for outcomes and drive initiatives to completion.
• Customer Obsession: You understand that our success is measured by our customers’ success.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

As a Customer Data Scientist at Datadog, you will partner directly with customers to help them design, execute, and scale high-impact experimentation programs. This role is ideal for someone with deep experience in applied experimentation who thrives in customer-facing environments and is motivated by driving measurable business outcomes. You will guide customers through experiment design, metric development, and data validation, helping them build trustworthy, decision-driven experimentation practices. Working cross-functionally with Sales, Product, and Engineering, you’ll play a key role in both customer success and product evolution.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Serve as a technical and analytical partner to customers across pre-sales and post-sales engagements, demonstrating the value of Datadog’s experimentation capabilities
• Support proofs of concept by helping customers define metrics, validate data pipelines, and design statistically sound experiments
• Educate customers on best practices in experiment design and interpretation across product, marketing, pricing, and AI-driven use cases
• Enable long-term customer success by building strong experimentation practices and analytical rigor within their teams
• Collaborate with Product and Engineering to translate customer feedback into product improvements and roadmap input
• Partner with Sales and Solutions teams to navigate complex customer needs, address objections, and build trusted relationships

Who You Are:

• 4+ years of experience in data science with a strong foundation in statistics, causal inference, and experimental design in applied business or product contexts
• Hands-on experience running A/B tests and applying advanced experimentation methods such as holdouts, bandits, synthetic controls, or geo-based testing
• Fluent in SQL and comfortable working with data warehouses and pipelines to diagnose and resolve data quality issues
• Experienced in customer-facing, consulting, or pre-sales environments, with the ability to communicate complex ideas clearly to diverse audiences
• Skilled at translating analytical insights into business impact, influencing decisions across technical and non-technical stakeholders
• Experience with experimentation platforms, analytics tooling, or modern data stack technologies (e.g., dbt, Airflow) is a plus

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

 
Benefits and Growth:

• Generous and competitive benefits package
• New hire stock equity (RSUs) and employee stock purchase plan
• Continuous career development and pathing opportunities
• Employee-focused best in class onboarding
• Internal mentor and cross-departmental buddy program
• Friendly and inclusive workplace culture
  
  

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard.
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Employee Equity Plan
• Generous professional development allowance
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• We offer free German courses at beginning, intermediate and advanced
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Comprehensive health benefits including medical, dental, and vision plans, as well as mental health resources
• Robust 401k program
• Employee Equity Plan
• Generous professional development allowance
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• 16 paid weeks for all parents (birthing and non-birthing), regardless of gender, to welcome newborns, adopted and foster children
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

We are seeking a Senior Software Engineer to join our Reference Data team in the Unified Platform (UP) organization as part of our efforts to build a mid-frequency platform. UP consolidates data and technologies into a comprehensive solution, accelerating time to market. Optimizing decision-making and research, our platform simplifies implementing new ideas, enhancing our competitive edge.

As a Senior Software Engineer on one of the Unified Platform teams, you'll be part of a tight knit team of software engineers working closely with internal users (analysts, quants, traders) to develop innovative systems that enable research and trading. You'll experiment with emerging technologies to process data at scale. You’ll wrestle a mountain of data into human understandable insights. 

We care deeply about preserving a respectful and diverse team culture. We are a group of polyglots and technologists always seeking to find the right tool for each problem, even if that means learning something new or reviving something old. We value business impact and outcomes over process, and we make decisions based on data. We strive to adapt quickly as business priorities change. 

What you’ll do in this role:

• Build and evolve data and platform capabilities that support mid-frequency trading research workflows
• Partner closely with internal customers to understand their needs and build intuitive self-service tools
• Develop software for large scale data acquisition, storage, accessibility, and visualization
• Design and operate scalable pipelines and platforms using modern "big data" and lakehouse patterns
• Improve reliability, observability, performance, and ergonomics across platform services
• Learn about market microstructure, financial instruments, and markets in which DRW participates or wants to participate in

This could be a good fit if you:

• Are motivated to solve hard problems with deceptively simple solutions
• Think a lot about user experience and try to really understand end users’ jobs and pain points
• Think a lot about APIs, modular design and testing
• Love refactoring and keep trying until you find a better answer
• Enjoy making the “right way to do it” the path of least resistance
• Have made a random tool for yourself…and then peers ask for it…then other teams ask for it…
• Are fiercely proud of your project’s reliability, performance and ease of maintenance

What we need on the team:

• 5+ years of platform-level software development experience
• Strong computer science fundamentals; a degree in Computer Science or equivalent work experience
• Financial market & reference data familiarity — understanding instrument IDs, feed normalization etc.
• Experience building research platforms and/or supporting mid-frequency trading environments
• Comfort working within a globally-distributed team
• A background in some of the following a bonus:
• Big data technologies: Spark, Delta Lake, Iceberg, Kafka, Airflow and/or Argo Workflows
• SQL and data warehousing/lake querying patterns
• Cloud-native deployments: AWS, Docker, Kubernetes
• Observability: Splunk, Prometheus, Grafana, Sentry

Location: This position is hybrid and can sit in Chicago, London, or New York City.

The annual base salary range for this position is $175,000 to $225,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

[#LI-TL1] 

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

As a Senior Data Engineer on our Data Experience team, you will play an integral role in bringing vendor datasets into our data platform, governing our centralized data pipelines, consolidating data delivery infrastructure across disparate systems, and working alongside individual Traders, Quantitative Researchers, and Back-Office personnel to best utilize the firm’s data and platform tools.

Technical requirements summary:

• Have extensive experience designing and building data pipelines
• Have experience working within modern batch and streaming data ecosystems
• An expert in SQL and Java or Python
• Extensive knowledge of data modeling techniques
• Able to own the delivery of data products, working with analysts and stakeholders to understand requirements and implement solutions
• Able to contribute to project management and project reporting
• Have experience driving nontrivial data migrations across platforms
• Able to establish, follow, and enforce data modeling standards across a large ecosystem.

What you will do in this role:

• Model, build, and manage data products built atop DRW’s Unified Data Platform.
• Work closely with Data Strategists to determine appropriate data sources and implement processes that onboard and manage new datasets for trading, research, and back-office purposes.
• Design data governance processes that enable discovery, cost-sharing, usage tracking, access controls, and quality control of datasets to address the needs of DRW trading teams and strategies.
• Continually monitor data ingestion pipelines and data quality to ensure stability, reliability, and quality of the data. Design monitoring and quality control software and processes.
• Own the technical aspects of vendor ingestion pipelines, coordinating with vendor relationship managers on upcoming changes, performing routine data operations without breaking internal users, and contributing to the team’s on-call rotation to respond to unanticipated changes.
• Rapidly respond to user requests, identifying platform gaps, and self-service opportunities that make the user experience more efficient.

What you will need in this role:

• 7+ years of experience working with modern data technologies and building data-first products.
• Excellent written and verbal communication skills.
• Proven ability to work in a collaborative, agile, and fast-paced environment, prioritizing multiple tasks and projects, and efficiently handle the demands of a trading environment.
• Proven ability to deliver rapid results within processes that span multiple stakeholders.
• Strong technical problem-solving skills.
• Extensive familiarity with SQL and Java or Python, with a proven ability to develop and deliver maintainable data transformations for production data pipelines.
• Experience leveraging data modeling techniques and ability to articulate the trade-offs of different approaches.
• Experience with one or more data processing technologies (e.g. Flink, Spark, Polars, Dask, etc.).
• Experience with multiple data storage technologies (e.g. S3, RDBMS, NoSQL, Delta/Iceberg, Cassandra, Clickhouse, Kafka, etc.) and knowledge of their associated trade-offs.
• Experience with multiple data formats and serialization systems (e.g. Arrow, Parquet, Protobuf/gRPC, Avro, Thrift, JSON, etc.).
• Experience managing data pipeline orchestration systems (e.g. Kubernetes, Argo Workflows, Airflow, Prefect, Dagster, etc.), delving deeply into low-level details.
• Proven experience in managing the operational aspects of large data pipelines such as backfilling datasets, rerunning batch jobs, monitoring event throughput, and handling dead-letter queues.
• Prior experience triaging data quality control processes, correcting data gaps and inaccuracies.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

[#LI-TL1] 

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

About the Team

The DRW C/FICCO Data Engineering team is essential to developing valuable datasets and scalable data infrastructure critical to our trading operations. We work closely with traders, researchers, and other engineering teams to ensure seamless data flow and accessibility, supporting data-driven decision-making. Our systems are designed to handle large volumes of data, maintain quality and integrity, and provide robust APIs for fast, ergonomic data retrieval.

About the Role

In this role you will:

• Collaborate with cross-functional teams to deliver data solutions that support diverse trading activities.
• Take full ownership of data products, guiding them from initial concept through to stable production.
• Design, build, and maintain systems for both batch processing and real-time streaming of time series datasets, ensuring high data quality and reliability.
• Develop APIs and data access methods for fast, intuitive retrieval of historical and live data, working with both new and existing systems.
• Provide on-call support as needed.

Qualifications:

• A minimum of 2+ years’ experience using at least one of Python, Java, and C++, and can work comfortably in multiple programming languages
• A track record of working directly with end customers, scoping and delivering production systems in fast-moving and ambiguous environments
• Ability to dive deep into complex problems, develop intuitive understandings, spot risks early, and minimize complexity
• Exceptional interpersonal skills - you communicate clearly with stakeholders as well as other engineers, fostering a collaborative, supportive working environment
• Experience in the financial markets, especially in delta one, store of value, and/or FICC options trading
• Experience with Linux-based, concurrent, high-throughput, low-latency software systems
• Experience with pipeline orchestration frameworks (e.g. Airflow, Dagster)
• Experience with streaming platforms (e.g. Kafka), data lake platforms (e.g. Delta Lake, Apache Iceberg), and relational databases
• Have a Bachelors or advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or equivalent work experience

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

#LI-BL1

The Role

As a Quant Developer at Man Group you will be part of one of our flagship teams in Man’s systematic trading arm - Man AHL. The team works hand-in-hand with Quant Researchers focusing on equity market neutral models. Your challenges will be varied, and will involve building new alphas and new trading strategies.

The Team

Quant Developers at Man Group are all part of our broader technology team, members of a group of over sixty individuals representing eighteen nationalities. We have varied backgrounds including Computer Science, Mathematics, Physics, Engineering – even Classics - but what unifies us is a passion for technology and writing high-quality code.

Our developers are organised into small cross-functional teams, with our engineering roles broadly of two kinds: “Quant Platform Developers” otherwise known as our “Core Techs”, and “Quant Developers” which we often refer to as “Sector Techs”. We use the term “Sector Tech” because some of our teams are aligned with a particular asset class or market sector. People often rotate teams in order to learn more about our system, as well as find the position that best matches their interests.

 
Our Technology

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the open-source libraries we use extensively. We implement the systems that require the highest data throughput in Java and C++.

We use Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker and Kubernetes for containerisation, OpenStack for our private cloud, Ansible and Terraform for architecture automation, and Slack for internal communication. We heavily utilise ArcticDB (https://arcticdb.io/) our in-house developed DataFrame Database. Our technology list is never static: we constantly evaluate new tools and libraries.

 
Technology and Business Skills

At AHL we strive to hire only the brightest and best and most highly skilled and passionate technologists.

Essential

• Exceptional technology skills; recognised by your peers as an expert in your domain
• A keen interest and understanding of financial markets and instruments
• A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing, refactoring and related approaches
• Strong knowledge of Python
• Proficient on Linux platforms with knowledge of various scripting languages
• Experience of data analysis techniques along with relevant libraries e.g. NumPy/SciPy/Pandas
• Relevant mathematical knowledge e.g. statistics, asset pricing theory, optimisation algorithms

Advantageous

• Experience of front office quantitative software development e.g. in a hedge fund or investment bank
• Experience of web based development and visualisation technology for portraying large and complex data sets and relationships
• Experience of machine learning techniques, natural language processing and related libraries and frameworks e.g. scikit-learn, Tensorflow

 
Personal Attributes

• Strong academic record and a degree with high mathematical and computing content e.g. Computer Science, Mathematics, Engineering or Physics from a leading university
• Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others
• Demonstrable passion for technology e.g. personal projects, open-source involvement
• Intellectually robust with a keenly analytic approach to problem solving
• Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities
• Focused on delivering value to the business with relentless efforts to improve process
• Strong interpersonal skills; able to establish and maintain a close working relationship with quantitative researchers, traders and senior business people alike
• Confident communicator; able to argue a point concisely and deal positively with conflicting views

 
Working Here

Man Group has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do.  We are actively engaged with the broader technology community.

• We host and sponsor London’s PyData and Machine Learning Meetups
• We open-source some of our technology. See github.com/man-group
• We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @ManQuantTech

We’re fortunate enough to have a fantastic open-plan office overlooking the River Thames, and continually strive to make our environment a great place in which to work. We believe that agile working allows us to deliver the best business outcomes for our clients and investors as well as having a positive impact on life / work balance and the wellbeing of our staff. We are simultaneously committed to "levelling the playing field" and believe that agile working promotes inclusivity across teams, regions and business units.

• We organise regular social events, everything from photography through climbing, karting, wine tasting and monthly team lunches
• We have annual away days and off-sites for the whole team
• As well as PC’s and Macs, in our office you’ll also find numerous pieces of cool tech such as light cubes and 3D printers, guitars, ping-pong and table-football, and a piano

We offer competitive compensation, a generous holiday allowance, various health and other flexible benefits. We are also committed to continuous learning and development via coaching, mentoring, regular conference attendance and sponsoring academic and professional qualifications.

Senior Data Engineer 

Who we are

Artefact is a new generation of data service provider, specialising in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.

Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 1000+ client base around the globe.

We have over 2000 employees across 26 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client.

Job Summary

We are looking for a Senior Data Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment. 

Key Responsibilities

• Design, build, and maintain scalable and robust data pipelines using SQL and Python, and leveraging any of the following: Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark.
• Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms.
• Implement continuous integration and continuous deployment (CI/CD) practices for data pipelines to improve efficiency and quality of data processing.
• Work closely with data architects, analysts, and other stakeholders to understand business requirements and translate them into technical implementations.
• Oversee and manage a team of data engineers, providing guidance and mentorship to ensure high-quality project deliverables.
• Develop and enforce best practices in data governance, security, and compliance within the organisation.
• Optimise data retrieval and develop dashboards and reports for business teams.
• Continuously evaluate new technologies and tools to enhance the capabilities of the data engineering function.

Qualifications

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
• 3+ years of industry experience in data engineering with a strong technical proficiency in SQL, Python, and big data technologies.
• Expertise in building scalable data workflows using cloud-native orchestration tools and distributed data processing frameworks.
• Demonstrated experience with Infrastructure as Code tooling such as Terraform
• Solid understanding of CI/CD principles and DevOps/DevSecOps practices.
• Proven leadership skills and experience managing data engineering teams.
• Excellent problem-solving skills and the ability to work with ambiguity.
• Proficient in leveraging AI-assisted workflows to optimise task efficiency.
• Strong communication and interpersonal skills.
• Excellent understanding of data architecture involving data mesh, data lake, data warehouse and data lakehouse.

Preferred Qualifications:

• Certifications in Azure, AWS, or GCP.
• Certifications in Databricks, Snowflake or similar technologies.
• Experience in the leading large scale data engineering projects.

Working Conditions

• Hybrid work arrangement: two-three days per week working from the office

Senior Data Engineer 

Who we are

Artefact is a new generation of data service provider, specialising in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.

Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 1000+ client base around the globe.

We have over 2000 employees across 26 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client.

Job Summary

We are looking for a Senior Data Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment. 

Key Responsibilities

• Design, build, and maintain scalable and robust data pipelines using SQL and Python, and leveraging any of the following: Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark.
• Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms.
• Implement continuous integration and continuous deployment (CI/CD) practices for data pipelines to improve efficiency and quality of data processing.
• Work closely with data architects, analysts, and other stakeholders to understand business requirements and translate them into technical implementations.
• Oversee and manage a team of data engineers, providing guidance and mentorship to ensure high-quality project deliverables.
• Develop and enforce best practices in data governance, security, and compliance within the organisation.
• Optimise data retrieval and develop dashboards and reports for business teams.
• Continuously evaluate new technologies and tools to enhance the capabilities of the data engineering function.

Qualifications

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
• 3+ years of industry experience in data engineering with a strong technical proficiency in SQL, Python, and big data technologies.
• Expertise in building scalable data workflows using cloud-native orchestration tools and distributed data processing frameworks.
• Demonstrated experience with Infrastructure as Code tooling such as Terraform
• Solid understanding of CI/CD principles and DevOps/DevSecOps practices.
• Proven leadership skills and experience managing data engineering teams.
• Excellent problem-solving skills and the ability to work with ambiguity.
• Proficient in leveraging AI-assisted workflows to optimise task efficiency.
• Strong communication and interpersonal skills.
• Excellent understanding of data architecture involving data mesh, data lake, data warehouse and data lakehouse.

Preferred Qualifications:

• Certifications in Azure, AWS, or GCP.
• Certifications in Databricks, Snowflake or similar technologies.
• Experience in the leading large scale data engineering projects.

Working Conditions

• Hybrid work arrangement: two-three days per week working from the office

The Community You Will Be Part Of: 

Airbnb, a leader in travel and hospitality, is on a mission to create a world where anyone can belong anywhere. We offer unique accommodations and experiences, crafted and curated by locals. As we expand into new marketplaces for in-person experiences and services, we are on the lookout for driven and innovative individuals to help shape our growth trajectory.

The Difference You Will Make:

This Advanced Analytics role will develop and lead initiatives focused on ensuring we have the right international growth strategy. They will lead measurement, build tools, and develop insights leveraging a wide range of internal and external data sources to ensure the business is making the right decisions for both strategic direction and tactical execution.

The ideal candidate is someone with a strong data and analytics background. This person is curious, engaged, positive, and detail- and solutions-oriented. The world— and thus our industry— is changing quickly so the ideal candidate will be comfortable with responding promptly and changing course as needed when priorities and reporting needs shift. 

This role will be expected to be highly collaborative, and work regularly with multiple stakeholders and cross functional partners across Regional Teams, Policy, Supply, Finance, Data Science, Operations, Engineering, and Marketing.

The right candidate will already be recognized as a leader in the data and analytics field at this level, with a proven track record of using a range of strategies and disciplines to solve complex and ambiguous measurement problems for business teams. This person will also use their considerable experience with data and insights storytelling to influence large-scale strategic programs, and  be adept at leveraging AI technologies to accelerate and raise their craft.

You must be comfortable working in a global company, delivering counsel and guidance to senior leadership across the team and organization. The successful candidate will have solid experience creating internal advocacy and influencing multiple senior audiences on hard to communicate topics.

The Team You Will Join: 

The Global Markets & Policy Advanced Analytics team is building the data infrastructure, measurement systems, and self-service tools that will power Airbnb's international growth in 2026 and beyond. This is a greenfield opportunity to shape how global teams make nimbler decisions, moving from HQ-dependent reporting cycles to fast, local, data-driven action.

This role will partner directly with Global Markets regional teams combined with Finance and Supply to surface local insights, build scalable tooling, and drive measurable impact on core business metrics. The ideal candidate brings deep technical rigor, strong business instincts, and a bias toward proactively building things—not just analyzing them.

A Typical Day:                    

• Build and maintain self-service analytics tools and dashboards that help country teams monitor performance and act on local signals                                    
• Partner with regional leads to translate business questions into clear analytical frameworks and actionable insights                                                    
• Support measurement for local marketing programs — campaign tracking, incrementality testing, and MMM contributions                                                     
• Analyze international market data to identify and size growth opportunities across supply, demand, and behavioral signals                                               
• Collaborate with Engineering, Marketing, and Research to deliver on data and tooling needs within shared roadmaps                                                       
• Provide analytical support for local growth levers (incentives, promotions, merchandising) including targeting and measurement                                                                                                                                         

Your Expertise:                                                                                                                                                                                                                                                                                                                                 

• 4+ years in data science, analytics, or business intelligence — marketplace, e-commerce, or global consumer tech preferred
• Expert SQL; proficiency in Python or R                                                                                                                             
• Hands-on experience with A/B testing, causal inference, and incrementality measurement                                                                                  
• Experience building self-service data products used by non-technical stakeholders                                                                                      
• Familiarity with international / multi-market analytics contexts                                                                                                        
• Strong data storytelling — able to communicate findings clearly to business and senior audiences                                                                        
• Collaborative, low-ego, and execution-oriented; you measure success by the decisions your work influences                                                               
• Comfortable with modern data stack tools (dbt, Airflow, Tableau, Looker, or equivalent)                                                                                                                                                                                          

Nice to Have:                                                                                                                                                             

• Supply/demand or geo-based analytics experience                                                                                                                         
• Growth marketing analytics (SEM, paid social, performance channels)
• Familiarity with MMM, attribution, or campaign measurement frameworks                                                                                                   
• Awareness of AI/LLM trends and implications for organic traffic and demand      

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

The Community You Will Be Part Of: 

Airbnb, a leader in travel and hospitality, is on a mission to create a world where anyone can belong anywhere. We offer unique accommodations and experiences, crafted and curated by locals. As we expand into new marketplaces for in-person experiences and services, we are on the lookout for driven and innovative individuals to help shape our growth trajectory.

The Difference You Will Make:

This Advanced Analytics role will develop and lead initiatives focused on ensuring we have the right international growth strategy. They will lead measurement, build tools, and develop insights leveraging a wide range of internal and external data sources to ensure the business is making the right decisions for both strategic direction and tactical execution.

The ideal candidate is someone with a strong data and analytics background. This person is curious, engaged, positive, and detail- and solutions-oriented. The world— and thus our industry— is changing quickly so the ideal candidate will be comfortable with responding promptly and changing course as needed when priorities and reporting needs shift. 

This role will be expected to be highly collaborative, and work regularly with multiple stakeholders and cross functional partners across Regional Teams, Policy, Supply, Finance, Data Science, Operations, Engineering, and Marketing.

The right candidate will already be recognized as a leader in the data and analytics field at this level, with a proven track record of using a range of strategies and disciplines to solve complex and ambiguous measurement problems for business teams. This person will also use their considerable experience with data and insights storytelling to influence large-scale strategic programs, and  be adept at leveraging AI technologies to accelerate and raise their craft.

You must be comfortable working in a global company, delivering counsel and guidance to senior leadership across the team and organization. The successful candidate will have solid experience creating internal advocacy and influencing multiple senior audiences on hard to communicate topics.

The Team You Will Join: 

The Global Markets & Policy Advanced Analytics team is building the data infrastructure, measurement systems, and self-service tools that will power Airbnb's international growth in 2026 and beyond. This is a greenfield opportunity to shape how global teams make nimbler decisions, moving from HQ-dependent reporting cycles to fast, local, data-driven action.

This role will partner directly with Global Markets regional teams combined with Finance and Supply to surface local insights, build scalable tooling, and drive measurable impact on core business metrics. The ideal candidate brings deep technical rigor, strong business instincts, and a bias toward proactively building things—not just analyzing them.

A Typical Day:                    

• Build and maintain self-service analytics tools and dashboards that help country teams monitor performance and act on local signals                                    
• Partner with regional leads to translate business questions into clear analytical frameworks and actionable insights                                                    
• Support measurement for local marketing programs — campaign tracking, incrementality testing, and MMM contributions                                                     
• Analyze international market data to identify and size growth opportunities across supply, demand, and behavioral signals                                               
• Collaborate with Engineering, Marketing, and Research to deliver on data and tooling needs within shared roadmaps                                                       
• Provide analytical support for local growth levers (incentives, promotions, merchandising) including targeting and measurement                                                                                                                                         

Your Expertise:                                                                                                                                                                                                                                                                                                                                 

• 4+ years in data science, analytics, or business intelligence — marketplace, e-commerce, or global consumer tech preferred
• Expert SQL; proficiency in Python or R                                                                                                                             
• Hands-on experience with A/B testing, causal inference, and incrementality measurement                                                                                  
• Experience building self-service data products used by non-technical stakeholders                                                                                      
• Familiarity with international / multi-market analytics contexts                                                                                                        
• Strong data storytelling — able to communicate findings clearly to business and senior audiences                                                                        
• Collaborative, low-ego, and execution-oriented; you measure success by the decisions your work influences                                                               
• Comfortable with modern data stack tools (dbt, Airflow, Tableau, Looker, or equivalent)                                                                                                                                                                                          

Nice to Have:                                                                                                                                                             

• Supply/demand or geo-based analytics experience                                                                                                                         
• Growth marketing analytics (SEM, paid social, performance channels)
• Familiarity with MMM, attribution, or campaign measurement frameworks                                                                                                   
• Awareness of AI/LLM trends and implications for organic traffic and demand      

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

Are you a Senior Data Engineer with a passion to build, support & maintain digital marketing solutions that offers real value? Are you interested in working with the largest global brands and complex challenges in the media analytics space? Then you might be the Senior Data Engineer we’re looking for!

What will your day look like?

As our new Senior Data Engineer, you will become part of our growing Data Insights and Science team. Here, you will employ new technologies across multiple cloud platforms to help successful brands reach their next level in 1:1 retargeting, communication, and CRM. More specifically, your tasks include:

• Identify, collect, and integrate data from various sources by building high-quality data pipelines and data models for analytics and business intelligence (BI) purposes.
• Develop and optimize code to enable pipelines at minimum cost and ease of maintenance.
• Build monitoring procedures & tools to ensure solid ETL flows and data quality.
• Design processes and tools to correct ETL incidents.
• Collaborate with CRM developers, data scientists, data analysts, and product owners to ensure the supplied data supports the business initiatives.
• Consult our data analytics teams to ensure best practices on the technical use of data are followed.
• Design data architectures and collaborate in data migrations in cloud environments. 

Who are you going to work with?

You will join a team of highly skilled Architects, Data Scientists, and Consultants who are passionate about unlocking insights from data through analytics. You will also get to work closely with experts from other Technology, Creative, and Client Teams.

What do you bring to the table?

As a person, you have a team player mindset and an open-minded attitude. You can communicate ideas and technical topics honestly and clearly – also to non-experts – while respecting the views of others on the team. You are eager to understand and find solutions, allowing you to quickly adapt to changing situations and come up with new ideas.

At the same time, you solve problems in an analytical and pragmatic manner.

Moreover, you have:

• Experience in data engineering, big data, business intelligence, or data science. 
• Experience in Spark, Python, Scala, or similar.
• Excellent SQL skills enabling large-scale data transformation and analysis.
• A comprehensive understanding of cloud data warehousing, data pipelines and data transformation (extract, transform, and load) processes and supporting technologies such as Google Dataflow, Looker, DBT, EMR, CI/CD Pipelines, Airflow DAGs, and other analytics tools.
• Experience with cloud-based data infrastructures (Ideally GCP, but AWS or Azure would also suffice)
• Programming experience in Javascript, Python, or similar.
• Expertise in managing databases, including performance tuning, backup, and recovery.
• Solid knowledge of data quality management best practices, including data profiling, data cleansing, and data validation
• Knowledge of strengths and limitations of visualization tools (e.g. PowerBI, Tableau, Looker, etc.) in terms of data modeling in the visualization tools.
• Understanding of versioning control tools like GitHub to changes related to dbt models and transformations, ensuring that changes are tracked, documented, and reviewed by the appropriate stakeholders.
• Knowledge of applying data governance principles, policies, and practices that ensure data accuracy, consistency, and security
• Knowledge of Kubernetes would be an advantage

Personal skills:

• Strong desire to contribute towards keeping data tidy and well-organized
• Ability to think critically, identify issues autonomously, and propose corrective actions.
• Build great relationships with your team and stakeholders

A leader in personalized customer experiences

VML MAP is a world-leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper personalization at scale, marketing automation and CRM. With the brain of a consultancy, the heart of an agency and the power of technology and data, we work with some of the world's most admired brands to help them on their transformation journey to becoming truly customer-centric. Together, we are 1000 + technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.

A global network

We are part of the global VML network that encompasses more than 30,000 employees across 150+ offices in 60+ markets, each contributing to a culture that values connection, belonging, and the power of differences. 

#LI-EMEA

Job Summary:

This is a captivating and exciting time to join Partnerize. We are at a pivotal point in our tech progression, looking to significantly expand our technical estate, scale the platform, and replace existing legacy systems with modern solutions. You will play a vital role in the ongoing operationalisation and management of our entire platform portfolio found in our on-prem datacentres and AWS cloud: Partnerize, BrandVerity, Ascend, and our recent acquisition, Konnecto. While there will be a key focus on integrating and supporting Konnecto's advanced data and AI layers, a critical pillar of your mission will be spearheading the development of our enterprise on-prem containerisation solution. This initiative is designed to fundamentally shift our engineering culture towards a "you build it, you own it" model. By providing robust, automated container platforms, you will empower our Engineering teams to deploy quickly and independently, significantly reducing the bottleneck created by relying solely on the TechOps department.

We are looking for a Lead SRE who is both a deep technical expert and a capable mentor. In this role, your primary responsibility is ensuring our diverse, hybrid systems remain available, scalable, and secure. You will act as an authoritative Subject Matter Expert (SME), championing developer autonomy, driving IT systems security policies, and working closely with the security compliance team to protect our platforms from threats while driving continuous integration and delivery.This role will report into the SRE and Application Manager providing them with technical guidance and recommendations whilst being the technical lead for the SRE team.

The Team

You will be responsible for ensuring the continuous development and progression of team members. We are looking for a player/coach who can mentor, empower, and up-skill talent. We have a mix of technical generalists, specialists, and junior engineers; you will help identify their strengths and constructively develop areas of weakness, guiding their technological career paths as we transition to a DevOps-centric operating model.

The Operational Reality

You will operate in a fast-paced, high-velocity environment where your work directly and visibly shapes the company's architectural future. This requires a highly adaptable and pragmatic leader who can balance strategic project delivery with hybrid-estate maintenance. By applying modern incident management frameworks to troubleshooting and ticket management, you are responsible for ensuring all issues across our estate are addressed decisively and efficiently.

As a Lead SRE, You Will:

Strategic & Operational Management

• Developer Empowerment&Containerisation
• Collaborate on the design, build, and rollout of a robust containerisation strategy (Kubernetes/Docker). Your goal is to assist in delivering a platform that enables Engineering teams to take full ownership of their code from build to deployment.
• Reliability & Error Budgets
• Define Service Level Indicators (SLIs), set Service Level Objectives (SLOs), and manage Error Budgets to expertly balance feature velocity with platform stability.
• Hybrid Platform Engineering & Konnecto
• Build software and systems to manage platform infrastructure across on-prem and AWS. Take the lead technical role in integrating and modernising Konnecto's architecture, ensuring its data ingestion and AI logic layers scale securely.
• FinOps / Cloud Cost Optimisation
• Manage, monitor, and optimise cloud infrastructure spend across our hybrid environments, ensuring architectural decisions are both highly performant and cost-effective.
• CI/CD Pipeline Responsibility
• Responsible for the continuous improvement, continuous delivery, and continuous integration pipelines to facilitate rapid engineering velocity.

People Leadership & Talent Development

• Mentorship
• Deliver coaching sessions to the team and individuals, acting as a technical escalation point and fostering a culture of knowledge sharing.
• Workload Management
• Scope the work coming into the SRE team, prioritise hybrid-estate maintenance vs. project delivery, and delegate tasks to team members to ensure prompt resolution.

Security & Architecture

• Design&Threat Modelling
• Produce production-grade application security designs. Perform design reviews and threat modelling of our services and products.
• Security Strategy
• Drive improvements to Partnerize platforms' security through strategic planning, vulnerability assessments, and security testing.

Incident Management&Toil Reduction

Toil Reduction Champion toil reduction through automation, continually identifying manual, repetitive operational work and engineering it out of existence.

Post-Mortems & Escalation

Act as the ultimate escalation point for complex support incidents, participate in the On-Call rotation, lead blameless post-mortems, conduct Root Cause Analysis (RCA), and aggressively track metrics like Mean Time To Recovery (MTTR).

General Duties

• Consulting&Planning
• Participate in system design consulting, platform management, and capacity planning.
• Escalation Support
• Act as the ultimate escalation point for complex support incidents and assignments while maintaining a high level of quality.
• On-Call
• Participate in the On-Call Rotation.

Essential Knowledge, Skills and Experience

Core Competencies

• Technical Ability
• Highly proficient SME capable of reliably applying technical methods, leading cultural technical shifts (e.g., DevOps adoption), and supporting the development of new skills in colleagues.
• Problem Solving&Decision Making
• Capable of making decisions quickly and decisively, weighing options, and approaching problems methodically and innovatively.
• Communication&Influence
• Effectively communicates initiatives to all stakeholders and is capable of procuring buy-in for key transformational projects (like containerisation rollouts).

Technical Competencies

• Cloud, Hybrid & Containerisation
• Essential knowledge of hybrid architectures, managing both AWS and on-premise environments. Extensive hands-on experience designing and managing advanced containerisation environments using Docker, Kubernetes, and Argo Workflows to enable developer self-service.
• Konnecto Tech Stack & Data Pipelines
• Proven experience managing modern storage layers and databases, specifically MongoDB and Snowflake. Experience supporting complex data ingestion layers, including clickdata streams, S3 raw/parsed ingestion, and Airflow ETL.
• Programming & Automation
• Experience in automation languages (Python orBash).
• Deep understanding of GitHub and experience implementing or working alongside AI coding tools and practices.
• Knowledge of Infrastructure as Code (Terraform, Ansible).
• Security&Observability
• Experience with security in a DevOps environment. Experience managing observability stacks (e.g., Prometheus, Grafana, and Loki).
• Operations&Troubleshooting
• Exceptional Linux system administration skills. Highly proficient in troubleshooting, diagnosing, and independently solving issues using modern incident management frameworks.

Desirable Knowledge, Skills and Experience

The following skills or experiences are advantageous but not strictly required

• Innovation&Debt Management
• A keen interest in new technologies, specifically supporting development teams in the refactoring of technical debt.
• Legacy Databases
• Strong experience with relational databases (MySQL, PostgreSQL, Redis).
• Data Streaming
• Experience with data streaming and queuing technologies, specifically Apache Kafka and Druid.
• Web&Storage
• Knowledge of Nginx (or other web server technologies) and storage technologies like Gluster.

UK Benefits & Perks

• 25 days holiday in addition to bank holidays 
• Enhanced Parental Leave: 6 months full pay for birth parent, 4 weeks non-birth parent at full pay after one year employment
• 5 extra 'Partnerize Parental Days' each year
• Private Medical Insurance through Vitality 
• Enhanced pension contributions
• Cycle to Work scheme 
• Eye Care Vouchers 
• Life Assurance
• Enhanced Wellness Program including access to EAP, Wellness Coaching & Wellness Fridays program
• Regular company events and activities

Please note that the positions are based in London, United Kingdom — relocation and visa support is provided if required (only if already based in the United Kingdom or Europe). 


BEST WORK OF YOUR CAREER

Trade Republic is the largest savings platform in Europe - we operate in 18 countries, serving +10 million customers who trusted us with over 150B in assets. But we’re striving for more.

We have a bold mission to empower everyone to build wealth with easy, safe, and free access to financial systems. You will have the opportunity to grow your career by collaborating with a team of outstanding talents and state of the art technology to build a lasting, positive future for millions. 

WHAT YOU'LL BE DOING

You will join a product delivery team and be responsible for ingesting, modeling, and publishing data to scale our business. You will design and maintain data products, collaborate on success metrics, and ensure interoperability by leveraging a self-service analytics platform and adhering to best practices.

• Working closely with product and business stakeholders to define and build meaningful product metrics
• Developing analytical products such as data models, dashboards, reports and tooling to enable self-serve reporting and analysis for stakeholders.
• Improving our architecture (cloudbased and always evolving) based on what brings the most impact to cost reduction and speed, applying software engineering best practices
• Taking ownership of projects from scoping to delivery and adoption, working autonomously 

WHAT WE'RE LOOKING FOR

• At least 5 years of engineering experience with an analytical mindset
• Solid understanding of architectures, design principles and engineering best practices
• Experience across all stages of the data pipeline: ingestion, transformations, mart creation
• Experience with our tech stack is a bonus: S3/Snowflake/Airflow/Python/DBT

WHY YOU SHOULD APPLY NOW

Our culture rewards ownership, excellence, and high energy. We care deeply about outcomes and hold each other accountable - we’re here to win and fix one of the largest challenges Europeans face - closing the pension gap and democratising wealth. If this gets you fired up, reach out!

Senior Analytics Engineer 

Communication has changed for people. It’s changed for businesses, too.

Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences.

Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.

Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.

What is the opportunity?

Intercom’s AI Group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are extremely product-focussed. Our team of 50+ ML scientists, ML engineers, designers and researchers works in partnership with other teams across the whole company. We move to production fast, often shipping to beta within weeks of a successful offline test. 

We constantly run experiments and measure the success of our AI features. We use frequentist and Bayesian approaches. We create dashboards to track results. We dive deep into exactly how users are being successful, and have to tease out all sorts of complex user interactions. We have to deal with inherently stochastic AI products, and complex effects.

We are looking for a dedicated Analytics Engineer to join the AI Group to help us with that.

What will I be doing?

• Data Platform Development: Design, build, and manage scalable data pipelines and ETL processes to support a robust, analytics-ready data platform.
• Cross-functional Collaboration: Partner with ai analysts, ml scientists, engineers and business teams to understand data needs and ensure accurate, reliable & ergonomic data solutions.
• Data Strategy & Governance: Lead initiatives in data model development, data quality ownership, warehouse management, and production support for critical workflows.
• Advanced Analytics & Insights: Conducted data analysis and built custom models to support strategic business decisions and performance measurement.
• Automation & Optimization: Streamline data collection and reporting processes to reduce manual effort and improve efficiency.
• Innovation in Data Infrastructure: Created scalable solutions like unified data pipelines and access control systems to meet evolving organizational needs.
• Strategic Influence: Worked with partner teams to align data collection with long-term analytics and feature development goals.

About You

• You write advanced SQL with a preference for well-architected data models, optimized query performance, and clearly documented code
• You’re familiar with the modern data stack. dbt and Snowflake experience are a big plus.
• A growth mindset and eagerness to learn.
• You exhibit great judgment and sharp business and product instincts that allow you to differentiate essential versus nice-to-have and to make good choices about trade-offs
• You practice excellent communication skills, and you tailor explanations of technical concepts to a variety of audiences

Nice to haves

• Exposure to Apache Airflow or other DAG frameworks — we use Airflow to orchestrate and schedule all of our data workflows and transformations
• Worked in Tableau, Looker, or similar visualization/business intelligence platform
• Experience with operational tools and business systems such Google Analytics, Marketo, Salesforce, Segment, or Stripe
• Familiarity with Python

#LI-Hybrid

What's the opportunity? 

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production.

This is a high-ownership role for someone who thrives in ambiguity, is energized by solving complex real-world problems, and is motivated by seeing their work translate into tangible business impact.

What will I be doing? 

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.
• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.
• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.
• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).
• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What skills do I need? 

• Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.
• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.
• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.
• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.
• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.
• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What's the opportunity? 

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production.

This is a high-ownership role for someone who thrives in ambiguity, is energized by solving complex real-world problems, and is motivated by seeing their work translate into tangible business impact.

What will I be doing? 

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.
• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.
• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.
• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).
• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What skills do I need? 

• Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.
• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.
• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.
• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.
• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.
• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated. 
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What's the opportunity? 

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production.

This is a high-ownership role for someone who thrives in ambiguity, is energized by solving complex real-world problems, and is motivated by seeing their work translate into tangible business impact.

What will I be doing? 

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.
• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.
• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.
• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).
• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What skills do I need? 

• Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.
• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.
• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.
• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.
• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.
• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What is the opportunity?

Intercom’s AI Group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are extremely product-focussed. Our team of 50+ ML scientists, ML engineers, designers and researchers works in partnership with other teams across the whole company. We move to production fast, often shipping to beta within weeks of a successful offline test. 

We constantly run experiments and measure the success of our AI features. We use frequentist and Bayesian approaches. We create dashboards to track results. We dive deep into exactly how users are being successful, and have to tease out all sorts of complex user interactions. We have to deal with inherently stochastic AI products, and complex effects.

We are looking for a dedicated Analytics Engineer to join the AI Group to help us with that.

What will I be doing?

• Data Platform Development: Design, build, and manage scalable data pipelines and ETL processes to support a robust, analytics-ready data platform.
• Cross-functional Collaboration: Partner with ai analysts, ml scientists, engineers and business teams to understand data needs and ensure accurate, reliable & ergonomic data solutions.
• Data Strategy & Governance: Lead initiatives in data model development, data quality ownership, warehouse management, and production support for critical workflows.
• Advanced Analytics & Insights: Conducted data analysis and built custom models to support strategic business decisions and performance measurement.
• Automation & Optimization: Streamline data collection and reporting processes to reduce manual effort and improve efficiency.
• Innovation in Data Infrastructure: Created scalable solutions like unified data pipelines and access control systems to meet evolving organizational needs.
• Strategic Influence: Worked with partner teams to align data collection with long-term analytics and feature development goals.

About You

• You write advanced SQL with a preference for well-architected data models, optimized query performance, and clearly documented code
• You’re familiar with the modern data stack. dbt and Snowflake experience are a big plus.
• A growth mindset and eagerness to learn.
• You exhibit great judgment and sharp business and product instincts that allow you to differentiate essential versus nice-to-have and to make good choices about trade-offs
• You practice excellent communication skills, and you tailor explanations of technical concepts to a variety of audiences

Nice to haves

• Exposure to Apache Airflow or other DAG frameworks — we use Airflow to orchestrate and schedule all of our data workflows and transformations
• Worked in Tableau, Looker, or similar visualization/business intelligence platform
• Experience with operational tools and business systems such Google Analytics, Marketo, Salesforce, Segment, or Stripe
• Familiarity with Python

Benefits 

#LI-Hybrid

What is the opportunity?

Intercom’s AI Group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are extremely product-focussed. Our team of 50+ ML scientists, ML engineers, designers and researchers works in partnership with other teams across the whole company. We move to production fast, often shipping to beta within weeks of a successful offline test. 

We constantly run experiments and measure the success of our AI features. We use frequentist and Bayesian approaches. We create dashboards to track results. We dive deep into exactly how users are being successful, and have to tease out all sorts of complex user interactions. We have to deal with inherently stochastic AI products, and complex effects.

We are looking for a dedicated Analytics Engineer to join the AI Group to help us with that.

What will I be doing?

• Data Platform Development: Design, build, and manage scalable data pipelines and ETL processes to support a robust, analytics-ready data platform.
• Cross-functional Collaboration: Partner with ai analysts, ml scientists, engineers and business teams to understand data needs and ensure accurate, reliable & ergonomic data solutions.
• Data Strategy & Governance: Lead initiatives in data model development, data quality ownership, warehouse management, and production support for critical workflows.
• Advanced Analytics & Insights: Conducted data analysis and built custom models to support strategic business decisions and performance measurement.
• Automation & Optimization: Streamline data collection and reporting processes to reduce manual effort and improve efficiency.
• Innovation in Data Infrastructure: Created scalable solutions like unified data pipelines and access control systems to meet evolving organizational needs.
• Strategic Influence: Worked with partner teams to align data collection with long-term analytics and feature development goals.

About You

• You write advanced SQL with a preference for well-architected data models, optimized query performance, and clearly documented code
• You’re familiar with the modern data stack. dbt and Snowflake experience are a big plus.
• A growth mindset and eagerness to learn.
• You exhibit great judgment and sharp business and product instincts that allow you to differentiate essential versus nice-to-have and to make good choices about trade-offs
• You practice excellent communication skills, and you tailor explanations of technical concepts to a variety of audiences

Nice to haves

• Exposure to Apache Airflow or other DAG frameworks — we use Airflow to orchestrate and schedule all of our data workflows and transformations
• Worked in Tableau, Looker, or similar visualization/business intelligence platform
• Experience with operational tools and business systems such Google Analytics, Marketo, Salesforce, Segment, or Stripe
• Familiarity with Python

Benefits 

#LI-Hybrid

About Sony Music Entertainment

At Sony Music Entertainment, we fuel the creative journey. We’ve played a pioneering role in music history, from the first-ever music label to the invention of the flat disc record. We’ve nurtured some of music’s most iconic artists and produced some of the most influential recordings of all time.

Today, we work in more than 70 countries, supporting a diverse roster of international superstars, developing and independent artists, and visionary creators. From our position at the intersection of music, entertainment, and technology, we bring imagination and expertise to the newest products and platforms, embrace new business models, employ breakthrough tools, and provide powerful insights that help our artists push creative boundaries and reach new audiences. In everything we do, we’re committed to artistic integrity, transparency, and entrepreneurship.

Sony Music Entertainment is a member of the Sony family of global companies.

Sony Music's Product Design Engineering and Global Operations (PDEGO) Team is looking for a Software Engineer to join our D2C team in our King’s Cross office (London). Your work will power the technology that will support our artist, label, and merchandise stores worldwide.

As a Software Engineer with PDEGO:

What you'll do:

• Work with a cross-functional team to build products that empower artists and record labels across the globe
• Contribute to all tiers of our architecture to produce high quality, robust user experiences
• Write clean, tested, maintainable code
• Work closely with product management to understand client requirements
• Participate in re-architecture, refinement and technical design of various systems

Who you are:

• We’re seeking a Data Platform Software Engineer with 4+ years of experience in the following areas:
• Strong experience implementing distributed systems and scalable data solutions.
• Proficiency in a scripting language, such as Python, for data pipeline development and automation.
• Deep experience with various database and data warehousing technologies and query languages (we use Neo4j, Kafka, MySQL, Snowflake, Elasticsearch, and more).
• Experience designing, building, and maintaining robust ETL/ELT data pipelines, including orchestration tools like Airflow, for large-scale data ingestion and transformation.
• Experience with data transformation tools such as dbt (data build tool).
• Familiar with techniques for data quality monitoring and ensuring data reliability.
• Experience with microservices, APIs, and related standards such as REST and HTTP.
• Comfortable with AWS Cloud technologies and cloud-native data services.
• Experience with Terraform or similar Infrastructure as Code (IaC) tools for managing and provisioning cloud resources.
• Experience using log analysis and monitoring tools to investigate data issues and pipeline performance.
• Experience writing unit and integration tests to ensure data integrity.
• Experience working in an agile team.

P-1534

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

As an Engineering Manager, you will work with your team to build mission-critical Lakebase services on the Databricks Platform at scale.

Key responsibilities include:

• Drive continuous delivery within a team of experts in storage technology, distributed systems and Rust.
• Manage the development and rollout of storage services that host millions of customer databases across dozens of regions
• Partner with peer engineering teams across Databricks to co-evolve Lakebase services with our global infrastructure.
• Lead operational excellence in 24/7 operation of our system

The impact you will have:

• Hire great engineers to build an outstanding team.
• Support engineers in their career development by providing clear feedback and develop engineering leaders.
• Ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence).
• Work with engineering and product leadership to build a long-term roadmap.
• Coordinate execution and collaborate across teams to unblock cross-cutting projects.

What we look for:

• Experience with building and shipping storage systems where correctness and performance are essential
• BS (or higher) in Computer Science, or a related field
• 2+ years of experience building and leading a team of engineers working in a related system
• Experience with build, release and deployment infrastructure technologies such as Spinnaker, Jenkins, Airflow, Docker, Kubernetes, Terraform, Bazel, etc.
• Ability to attract, hire, and coach engineers who meet the Databricks hiring standards - can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members; can gain trust of the team and guide their careers
• Comfort working on cross-functional projects with the ability to deeply understand product and customer personas

Team

As an engineering team, we believe strongly that empathy improves our solutions. Seeing how people use the product is a priority and the way we get to the right answer. Engineers will have the opportunity to work closely with our team onsite to understand the variety of use cases that Peregrine serves.

The Foundations team consists of detail-oriented engineers driving innovation and enhancing performance through technical excellence and a focus on results. We own the performance of Peregrine's mission-critical infrastructure as well as the high-risk, platform-spanning initiatives that create unmatched new capabilities.

We value both ownership and collaboration—you will take full responsibility for major features and work closely with other engineers to drive them to completion. We believe that humility and empathy are essential for building the right solutions—you will collaborate directly with our deployment team and users as we iterate to solve their problems. Perseverance and creativity are crucial to executing our vision.

Role

As the first Software Engineer in the UK, you'll have vast ownership across our stack, making decisions that will have an outsized impact for years to come.

You'll push the boundaries of what a data platform can do by creating novel capabilities that span the platform and optimizing subsystems to achieve order-of-magnitude improvements in performance. You will work on projects such as re-architecting our Elasticsearch cluster, taking response times from seconds to milliseconds; and owning other strategic initiatives that deliver industry-leading platform performance and capabilities.

Our stack is constantly evolving but based on a backend foundation of Python, Django, Celery, Airflow, and Kafka; a frontend built in React, Redux, and Mapbox; data stores including PostgreSQL and Elasticsearch; machine learning models hosted in Bedrock and Sagemaker; and with AWS, Pulumi, Terraform, and Kubernetes as our underlying infrastructure.

About you

• Desire and drive to own large portions of the application from start to finish
• Passion for crafting and shipping software solutions that delight users
• Thrive on ambiguity and love taking on hard problems
• Excellent technical vision with the ability to synthesize product requests into strong and reliable software components

What we look for

• Degree in Computer Science or a related field, or equivalent experience
• 8+ years of experience working with cross-functional software development teams
• Experience shipping and iterating on production-grade software components professionally and/or in the open-source community
• Ability to write robust, well-tested, and well-designed code that frequently gets deployed to users
• Strong understanding of product development and navigating large codebases

Salary Range: £110,000 - £186,000 Annually + Benefits + Equity (if applicable) + Bonus (if applicable)

Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, certifications or licenses, and specific work location. Information on the benefits offered is here.

About Euc

We’re making good health last a lifetime

More than 1 billion people globally live with obesity, a significant leading indicator of many preventable chronic diseases such as diabetes and heart disease.

Eucalyptus is the company behind Juniper, one of the world’s largest weight management programs combining GLP-1 medication with a tailored nutrition and exercise programme, supported by our multidisciplinary care team of prescribers, health coaches, dietitians, nurses and pharmacists.

Our published clinical research demonstrates that our combined approach to weight management and lifestyle change increases the likelihood of our patients losing significant weight during their treatment with Juniper by four times.

Since launching, we’ve grown fast to support millions of patients. In the last 12 months:

• We grew the size of our patient base by 10x in the UK, received selective NICE endorsement for our holistic approach to obesity management, and grew our team from 50 to 200.
• Globally, we grew revenue by >120% YoY, while reducing cash burned by 90% YoY, with over $100M USD raised from global investors such as BOND, NewView, Blackbird and Airtree - early backers of companies like Canva, Stripe, Uber and Airbnb.

What’s next?

In 2025, we are charting the path to support hundreds of thousands of patients while launching into new conditions, demographics, and geographies as we move towards our vision of creating a preventive healthcare ecosystem.

We’re building the world’s largest international digital healthcare company. This will be highly challenging, very rewarding and the adventure of a lifetime, working with the best operators you will ever encounter.

If that gets you excited, let’s talk!

About the Role

We’re looking for a Senior Data Engineer to join our growing UK data team. This role combines hands-on engineering with real business impact: you’ll provide core data engineering support for the UK market, while also building novel data pipelines to unlock optimisation, personalisation, and advanced analytics across our data stack.

You’ll work closely with data analysts, operations, marketing, and product teams to ensure our data is reliable, accessible, and actionable — helping us deliver more personalised healthcare experiences at scale.

What You’ll Do

• Own and maintain data pipelines that serve the UK business, ensuring accuracy, reliability, and efficiency.
• Partner with analysts and data scientists to deliver clean, well-modelled datasets for reporting and experimentation.
• Design and build new data pipelines that enable optimisation and personalisation (e.g. user segmentation, recommendation features, lifecycle targeting).
• Collaborate with global engineering and platform teams to align on standards while advocating for UK-specific requirements.
• Work with functional teams to provide bespoke solutions for specific use cases, including streaming reporting & analytics, real-time data pipelines, and inference and personalisation services.

About You

• 6+ years of experience in data engineering or similar roles.
• Strong proficiency in SQL and modern data warehouses (BigQuery, Snowflake, or Redshift).
• Hands-on experience with orchestration tools (Airflow, Dagster) and ETL/ELT pipelines/tools (dbt).
• Familiarity with cloud platforms (preferably GCP)
• Comfortable with Python for data transformation and pipeline development.
• Ability to distil requirements into a clear, bespoke solution that creates sustainable value
• Strong communication skills — able to work with both technical and non-technical stakeholders.

So, why join Eucalyptus?

• Make real impact, fast - We build in the open together, which helps us learn and iterate more quickly to deliver high-quality outcomes faster than anyone else. Helping impact patients’ lives for the better from the moment you join Euc.
• You’ll be supported to accelerate your career - Regular feedback alongside our bi-annual performance reviews, a professional development budget & leave help ensure you have the support you need to level up. We’re committed to helping every Eucalypt reach their full potential.
• You’ll work with others who are incredibly passionate about what they do - Our talent bar is high, and our work ethic is strong. You’ll get to stretch yourself every day, be given autonomy to tackle interesting problems, and work amongst people who care deeply about our patients.
• We also offer a range of benefits including
  • Your own stake in the business with our employee options program
  • Newly opened HQ in vibrant Old Street, designed for focus and collaboration
  • A flexible hybrid setup: 3 days a week in our Old Street office
  • A monthly wellness allowance, for you to spend on whatever wellness means to you
  • A yearly personal development budget and 3 extra days of leave to continuously up-skill yourself
  • 25 days holiday + bank holidays with an enhanced parental leave policy
  • A fun office with regular socials including after-school sport, clubs, cycle kick-offs, and seasonal parties. We had our winter social in Paris last year! 🇫🇷
  • Your own MacBook and more!
• Want to hear more about what it’s like to work at Eucalyptus? Hear from our team here or check us out on Instagram @eucalyptus.health

At Eucalyptus, we value individuals from all backgrounds, experiences, and perspectives, and we embrace the unique qualities each person brings. When you apply, please let us know of any reasonable adjustments you may need during the interview process.

About Euc

We’re making good health last a lifetime

More than 1 billion people globally live with obesity, a significant leading indicator of many preventable chronic diseases such as diabetes and heart disease.

Eucalyptus is the company behind Juniper, one of the world’s largest weight management programs combining GLP-1 medication with a tailored nutrition and exercise programme, supported by our multidisciplinary care team of prescribers, health coaches, dietitians, nurses and pharmacists.

Our published clinical research demonstrates that our combined approach to weight management and lifestyle change increases the likelihood of our patients losing significant weight during their treatment with Juniper by four times.

Since launching, we’ve grown fast to support millions of patients. In the last 12 months:

• We grew the size of our patient base by 10x in the UK, received selective NICE endorsement for our holistic approach to obesity management, and grew our team from 50 to 200.
• Globally, we grew revenue by >120% YoY, while reducing cash burned by 90% YoY, with over $100M USD raised from global investors such as BOND, NewView, Blackbird and Airtree - early backers of companies like Canva, Stripe, Uber and Airbnb.

What’s next?

In 2025, we are charting the path to support hundreds of thousands of patients while launching into new conditions, demographics, and geographies as we move towards our vision of creating a preventive healthcare ecosystem.

We’re building the world’s largest international digital healthcare company. This will be highly challenging, very rewarding and the adventure of a lifetime, working with the best operators you will ever encounter.

If that gets you excited, let’s talk!

About the Role

We’re looking for a Mid-level Data Engineer to join our growing UK data team. This role combines hands-on engineering with real business impact: you’ll provide core data engineering support for the UK market, while also building novel data pipelines to unlock optimisation, personalisation, and advanced analytics across our data stack.

You’ll work closely with data analysts, operations, marketing, and product teams to ensure our data is reliable, accessible, and actionable — helping us deliver more personalised healthcare experiences at scale.

What You’ll Do

• Own and maintain data pipelines that serve the UK business, ensuring accuracy, reliability, and efficiency.
• Partner with analysts and data scientists to deliver clean, well-modelled datasets for reporting and experimentation.
• Design and build new data pipelines that enable optimisation and personalisation (e.g. user segmentation, recommendation features, lifecycle targeting).
• Collaborate with global engineering and platform teams to align on standards while advocating for UK-specific requirements.
• Work with functional teams to provide bespoke solutions for specific use cases, including streaming reporting & analytics, real-time data pipelines, and inference and personalisation services.

About You

• 4+ years of experience in data engineering or similar roles.
• Strong proficiency in SQL and modern data warehouses (BigQuery, Snowflake, or Redshift).
• Hands-on experience with orchestration tools (Airflow, Dagster) and ETL/ELT pipelines/tools (dbt).
• Familiarity with cloud platforms (preferably GCP)
• Comfortable with Python for data transformation and pipeline development.
• Ability to distil requirements into a clear, bespoke solution that creates sustainable value
• Strong communication skills — able to work with both technical and non-technical stakeholders.

So, why join Eucalyptus?

• Make real impact, fast - We build in the open together, which helps us learn and iterate more quickly to deliver high-quality outcomes faster than anyone else. Helping impact patients’ lives for the better from the moment you join Euc.
• You’ll be supported to accelerate your career - Regular feedback alongside our bi-annual performance reviews, a professional development budget & leave help ensure you have the support you need to level up. We’re committed to helping every Eucalypt reach their full potential.
• You’ll work with others who are incredibly passionate about what they do - Our talent bar is high, and our work ethic is strong. You’ll get to stretch yourself every day, be given autonomy to tackle interesting problems, and work amongst people who care deeply about our patients.
• We also offer a range of benefits including
  • Your own stake in the business with our employee options program
  • Newly opened HQ in vibrant Old Street, designed for focus and collaboration
  • A flexible hybrid setup: 3 days a week in our Old Street office
  • A monthly wellness allowance, for you to spend on whatever wellness means to you
  • A yearly personal development budget and 3 extra days of leave to continuously up-skill yourself
  • 25 days holiday + bank holidays with an enhanced parental leave policy
  • A fun office with regular socials including after-school sport, clubs, cycle kick-offs, and seasonal parties. We had our winter social in Paris last year! 🇫🇷
  • Your own MacBook and more!
• Want to hear more about what it’s like to work at Eucalyptus? Hear from our team here or check us out on Instagram @eucalyptus.health

At Eucalyptus, we value individuals from all backgrounds, experiences, and perspectives, and we embrace the unique qualities each person brings. When you apply, please let us know of any reasonable adjustments you may need during the interview process.

About the role           

Anthropic is looking for a Data Engineer to join the Safeguards team and build the data foundations that keep our AI systems safe. The Safeguards team works to monitor models, prevent misuse, and ensure user well-being — and doing that well requires robust, reliable data infrastructure. In this role, you'll design and build the data pipelines, warehousing solutions, and analytical tooling that power our safety and trust efforts at scale.

You'll work closely with engineers, data scientists, and policy teams to ensure the Safeguards organization has the data it needs to detect abuse patterns, measure the effectiveness of safety interventions, and make informed decisions about model behavior and enforcement. This is a high-impact role where your work will directly support Anthropic's mission to develop AI that is safe and beneficial.

Responsibilities:

- Design, build, and maintain scalable data pipelines that support safety monitoring, abuse detection, and enforcement workflows
- Develop and optimize data models and warehousing solutions to enable efficient analysis of large-scale usage and safety data
- Build and maintain dashboards and reporting infrastructure that give Safeguards teams visibility into model behavior, misuse patterns, and enforcement outcomes
- Collaborate with engineers to integrate data from multiple sources — including model outputs, user reports, and automated classifiers — into a unified analytical layer
- Implement data quality frameworks, monitoring, and alerting to ensure the reliability of safety-critical data
- Partner with research teams to surface data insights that inform model improvements and safety interventions
- Develop self-service data tooling that enables stakeholders to explore safety data and generate reports independently
- Contribute to data governance practices, including access controls, retention policies, and privacy-compliant data handling

You may be a good fit if you:

- Have 3+ years of experience in data engineering, analytics engineering, or a related role
- Are proficient in SQL and Python, with experience building and maintaining ETL/ELT pipelines
- Have hands-on experience with modern data stack tools such as dbt, Airflow, Spark, or similar orchestration and transformation frameworks
- Have worked with cloud data platforms (BigQuery, Redshift, Snowflake, or similar)
- Are comfortable building dashboards and data visualizations using tools like Looker, Tableau, or Metabase
- Communicate clearly and can translate complex data concepts for both technical and non-technical audiences
- Are results-oriented, flexible, and willing to pick up slack even when it falls outside your job description
- Care about the societal impacts of AI and are motivated by safety work

Strong candidates may have:

- Experience with trust & safety, integrity, fraud, or abuse detection data systems
- Experience with large-scale event streaming systems (Kafka, Pub/Sub, Kinesis)
- Built data infrastructure that supports ML model monitoring or evaluation
- Familiarity with data privacy and compliance frameworks (GDPR, CCPA, or similar)
- A background in statistical analysis, or experience collaborating closely with data scientists
- Developed internal tooling or self-service analytics platforms

Strong candidates need not have:

- A formal degree in Computer Science or a related field — we value practical experience and demonstrated ability over credentials
- Prior experience in AI or machine learning — you'll learn the domain-specific context on the job
- Previous experience at an AI safety or research organization
- Deep expertise across every tool listed above — familiarity with a subset and a willingness to learn is enough

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs.

We’re building multi-step coding agents that can understand large codebases, plan changes, call tools, and iterate with the user. As a Research Engineer in the Agentic Models team, you’ll be responsible for the models, training loops, and evaluation pipelines that power these agents.

You’ll work at the intersection of SFT and RL-style post-training, and product-driven evaluation, using our distributed GPU and MapReduce clusters to ship models into JetBrains products.

As part of our team, you will:

• Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.
• Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.
• Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.
• Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and close the loop from evaluation back into training, data, and reward design.
• Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.
• Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.
• Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features. 

We’ll be happy to bring you on board if you have:

• Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.
• Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).
• Strong theoretical and practical understanding of LLM fundamentals: architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A product-aware mindset – you care about how developers actually use agents and can translate product needs and failure modes into modeling and evaluation work.
• At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM.
• Large-scale data and training pipelines, e.g. MapReduce-style clusters, multi-node GPU training, or workloads on the order of 1M+ CPU/GPU hours.
• Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.
• AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.
• Inference optimization and serving optimized models in production.

#LI-KP1

About Us

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We’re backed by Accel, Lightspeed, NfX and other top-tier investors.

Role Overview

We are seeking a talented Analytics Lead to build and lead our analytics function from the ground up. This role is crucial for establishing our core data infrastructure and delivering actionable insights across all teams to power strategic decision-making and drive business growth.

Key Responsibilities:

• Data Infrastructure & Governance:
  
  
• Design and implement our core analytics infrastructure, including data warehousing, ETL processes, and visualization tools.
• Establish data quality standards, automate routine reporting, and create self-service analytics tools to ensure data accuracy and accessibility.

• Business Intelligence & Insights:
  
  
• Create and maintain dashboards for key business metrics across operations, finance, partnerships, and growth teams.
• Develop comprehensive analytics for transaction monitoring, liquidity optimization, platform performance, and revenue forecasting.
• Analyze user behavior and transaction patterns to drive growth strategies.

• Risk & Financial Analytics:
  
  
• Build analytics models for pricing optimization and financial planning.
• Create risk monitoring systems and fraud detection analytics to ensure platform security.

• Strategic Partnership & Team Leadership:
  
  
• Partner with leadership to provide data-driven insights for strategic decision-making.
• Build, manage, and mentor a high-performing team of analysts as the organization scales.

What we are looking for

Must-haves:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
• 6+ years of experience in analytics or data science roles.
• Strong programming skills in Python and SQL.
• Experience with modern data stack tools (e.g., Snowflake, dbt, Airflow).
• Proven experience building and maintaining large-scale data pipelines.
• Excellent communication skills with the ability to present complex data to non-technical stakeholders.
• Strong problem-solving skills and meticulous attention to detail.

What helps you stand out:

• A Master's degree in a relevant field.
• Experience in a fintech or financial services environment.
• Direct experience with crypto/blockchain analytics.
• Startup experience is highly preferred.
• Expertise with data visualization tools like Tableau or Looker.

What We Offer

• Competitive salary and benefits package.
• Equity in a rapidly growing company.
• Opportunity to work in a fast-paced startup at the forefront of fintech innovation.
• Opportunity to make a significant impact on global financial infrastructure
• Collaborative work culture with emphasis on personal and professional growth.

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.