About the role

Starburst is looking for an experienced Staff Software Engineer to sit at the intersection of software engineering and data engineering — building the internal platforms, pipelines, and data products that power how we understand our customers and our business. You'll work across Starburst Enterprise and Starburst Galaxy, using our own technology to solve real problems at scale, while also contributing software that other teams depend on.

Because data engineers are one of our primary target personas, you'll bring a uniquely valuable perspective: you'll use our products daily and feed that experience directly back into how we build and improve them. You'll work closely with a dynamic, talented, globally distributed team, writing production-quality software alongside building reliable data systems — with a consistent emphasis on quality, maintainability, and speed to insight.

As a Staff Software Engineer at Starburst you will:

• Design, build, and operate a high-quality data lake and the software systems that feed it, supporting product management, finance, customer support, and engineering
• Write production-grade software — services, APIs, tooling, and automation — that enables data workflows and integrations at scale
• Find innovative ways to use Trino and Starburst to solve complex data management and software architecture challenges
• Collaborate with technical leads, product managers, and data analysts to build robust data products and analytics
• Leverage AI to democratize access to datasets for users throughout Starburst, including building and maintaining the software infrastructure that makes this possible
• Enable dataset preparation and model evaluation for Starburst's AI projects
• Define and evolve engineering processes and best practices that span both software and data domains, with a focus on reliability and actionable results
• Work closely with leaders across teams to iterate on data architecture and the software systems that implement it, keeping quality high at every layer
• Identify emerging patterns in data management and software engineering, and work with Starburst's product teams to bring those innovations to market

Some of the things we look for

• A Trino enthusiast looking to push the bounds in an AI future
• At least 7 years of combined experience in software engineering and/or data engineering, with genuine depth in both
• Strong software engineering fundamentals: writing clean, testable, well-reviewed code in Java, Python, or Scala
• Experience building and optimizing data pipelines using Trino, Spark, dbt, and related frameworks
• Experience designing and building backend services, APIs, and data platform components
• Experience managing data and application infrastructure in public clouds, particularly AWS (EMR, EC2, S3, IAM); multi-cloud experience (GCP/Azure) is a plus
• Experience using and managing orchestration frameworks such as Apache Airflow or Dagster
• Knowledge of RAG and other design patterns for AI-powered applications
• Fluency in SQL and comfort moving between SQL and general-purpose programming as the task demands
• Experience building API integrations for extracting data from third-party sources
• Knowledge of data modeling techniques appropriate for modern data lakes
• Proficiency with Configuration-as-Code and Infrastructure-as-Code tools such as Pulumi, Terraform, and/or Ansible
• A track record of shipping reliable software and data systems on time, with disciplined practices around testing, code quality, and review
• Strong written and verbal communication skills, with the organizational ability to coordinate across teams

Where could this role be based?

• San Francisco, US

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

The Data Office is responsible for data associated with products, AI, marketing, finance, sales, and more. Our department ensures that all teams at JetBrains have access to up-to-date, reliable, and transparent data and data services.

As part of our growth strategy, we are looking for an experienced, detail-oriented, and self-motivated BI Analyst to develop, maintain, and enhance BI reports and dashboards for our internal customers across corporate functions, including marketing, IT, PMO, and others.

As part of our team, you will:

• Design, develop, and automate reports and dashboards for several of our data domains, such as marketing, IT, and executive reporting.
• Partner with the Data Quality team to define and implement rules that ensure high data reliability standards.
• Continuously engage with other colleagues at JetBrains, including team clients, data partners, data engineers, and data analysts, to gather and refine business requirements.
• Promote best practices in data visualization.
• Participate in both business-driven and technical projects.

We’ll be happy to have you on our team if you have:

• Extensive SQL experience.
• At least three years of experience with Tableau – experience with Metabase or alternative BI tools is a plus.
• Strong knowledge of and experience with dbt.
• Strong attention to detail and the ability to identify small but important differences.
• Ability to work independently, take ownership of tasks, analyze problems, and deliver results within agreed-upon deadlines.
• Fluent English, both written and spoken.
• Proactive mindset.
• Dedication to knowledge sharing and cross-team collaboration.

We’ll be especially thrilled if you have:

• Basic experience in DWH development.
• Basic experience with AWS. 
• Experience in marketing, including marketing metrics, data structures, and marketing data.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. 
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI

#LI-KP1

This role is designed for a "Hub-and-Spoke" organizational model. The Head of Data will not manage the day-to-day tickets of embedded analysts but will own the Data Strategy, Infrastructure, and Standards that allow those analysts to be successful and consistent across the company.

Role Mission

As the Head of Data, the mission is to transform a decentralized data landscape into a unified, high-performance ecosystem. Head of Data will bridge the gap between autonomous product squads and a centralized data vision. Head of Data is the architect of our data culture, ensuring that while analysts sit within different business units, they operate with a common language, world-class tools, and uncompromised data integrity.

Key Responsibilities

Strategic Leadership & Governance

• Unified Data Strategy: Define and execute a global data roadmap that aligns with company-wide OKRs.
• Standardization: Define universal metrics (e.g., "Active User," "Revenue") to ensure a single source of truth across all departments.
• Data Governance: Set policies for data privacy, security, and compliance (GDPR) without bottlenecking the speed of the product teams.

Platform & Infrastructure

• Modern Data Stack: Own the selection and maintenance of our data warehouse (e.g., Snowflake/Redshift), transformation layers (dbt), and BI tools (Looker/Tableau).
• Data Engineering Oversight: Lead the core data engineering efforts to ensure a robust ETL/ELT pipeline that serves the decentralized "spokes."
• Self-Service Enablement: Build the infrastructure that allows non-technical stakeholders to access insights without needing an analyst for every query.

Functional Excellence & Community

• The Data Guild: Create and lead a "Data Guild" or "Community of Practice" to facilitate knowledge sharing, peer reviews, and mentorship among embedded analysts.
• Talent Bar: Define the hiring standards, leveling rubrics, and career paths for all data roles across the company. 
• Best Practices: Drive the adoption of version control (Git), documentation, and automated testing (Data Quality) within the analytic workflows.

Business Impact & Culture

• Data Literacy: Act as an evangelist for data-driven decision-making, coaching C-suite and Product Leads on how to better leverage data.
• Resource Allocation: Partner with Department Leads to identify where data gaps exist and advocate for the placement of analysts in the highest-impact areas.

Key Requirements

Strategic Leadership & Organizational Design

• Architectural Strategy: 6+ years of experience in Data/Analytics, with a proven track record of scaling "Hub-and-Spoke" or Data Mesh models. Demonstrated ability to balance centralized governance with decentralized execution speed.
• Strategic Influence: Proven ability to influence and align senior stakeholders (C-level, Product Leads) who do not have a direct reporting line to this role. Ability to lead through expertise and professional authority.
• Data-as-a-Product Mindset: A strategic approach to treating the data platform, tooling, and core datasets as internal products, where embedded analysts and business units are the primary customers.
• Change Management: Experience in leading organizational transitions (e.g., from centralized to decentralized) and establishing a high-performance data culture across distributed teams.

Technical Excellence & Methodology

• AI Modernization & Tooling: Lead the evaluation and strategic implementation of cutting-edge AI-driven data extraction solutions, ensuring selected technologies align with cross-departmental requirements and scale seamlessly across the organization’s data infrastructure.
• Modern Data Stack Mastery: Expert-level knowledge of cloud data warehousing (e.g., Snowflake, Redshift), transformation layers (dbt), and orchestration.
• Advanced Analytics & Modeling: Proficiency in SQL and Python/R for complex data modeling and predictive analytics. Deep understanding of version control (Git) and CI/CD practices in data workflows.
• Statistical Rigor & Experimentation: Extensive experience in designing and analyzing A/B tests, causal inference, and applying advanced statistical methods to drive business decisions.
• Operational Intelligence: Background in high-scale operational analytics, including forecasting, capacity planning, efficiency analysis, and automated quality assurance.

Functional Management & Governance

• Talent Development & Bar Raising: Experience in defining hiring standards, career frameworks, and mentorship programs for Data Analysts and Data Scientists.
• Data Governance & Quality: Proven ability to establish global data standards, master data management, and unified metric definitions to ensure a "Single Source of Truth" across the organization.
• Storytelling & Communication: Exceptional ability to translate complex technical findings into persuasive, executive-level narratives that drive operational and strategic improvements.
• Pragmatic Problem Solving: A results-oriented mindset with the ability to bridge the gap between high-level data science and pragmatic, actionable business solutions.

What we believe

At TransferGo, we offer competitive rewards to all people. We know that recognition is about more than just money, and we’ve fostered a culture of kudos to shine a light on the great work throughout the business, and the people making it all happen. We hold regular in-person events to connect with each other and help all our TransferNauts to grow with a generous training allowance. We believe that empowering people makes for a happier and more effective workforce. This means we enable anyone who wants to pursue initiatives that deliver real value for our migrant customers. 

What We Offer:

• Competitive Salary: Starting from 19 930-29 920 PLN (gross) per month, depending on experience. Salary is just one part of the conversation – if you’re excited about the role but the range feels slightly off, don’t hesitate to apply. We’re open to discussing based on your experience and potential.
• Comprehensive Benefits: Including a generous holiday allowance, competitive healthcare insurance, and a wellbeing package from day one.
• Annual Development Budget: €1,000 to invest in your personal and professional growth.
• Hybrid Working Environment: Flexibility to work from home and in the office, with most team members in the office two days a week.
• Pet-Friendly Office: If you’re near one of our offices, bring your furry friend along!
• Inclusive Culture: Regular in-person events, fostering a strong sense of community and collaboration.
• Empowerment and Ownership: We believe in empowering our people to take initiative and drive meaningful change.

We’re looking for a Software Engineer to join Bolt’s Data Platform Insights team. You’ll build and evolve the platform that helps Bolt teams create and manage high-quality data products — making data reliable and accessible, to power decisions at massive scale.

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

As a Software Engineer in the Insights team, you will play a vital role in shaping the data ecosystem at Bolt. You will deliver frameworks, libraries, and automations that make it effortless to build, test, and deploy thousands of data models, metrics, and BI reports.

You’ll work closely with data producers to turn their toughest challenges into scalable, elegant platform solutions. We’re solving complex engineering problems at scale to ensure that Bolt’s data modelling ecosystem stays reliable, cost-effective, and performant.

• You have 3–4 years of experience as a software or data engineer, and have hands-on experience building and deploying data pipelines or analytics workloads in cloud environments.
• You’re proficient in Python and SQL, developing production-ready code for internal libraries, data pipelines, and automation.
• You have excellent communication skills, are fluent in spoken and written English, and you’re comfortable collaborating with both technical and non-technical colleagues.
• You understand modern CI/CD practices and value automation, testing, and observability as core engineering principles.
• You’re driven by customer success - motivated by helping teams be more productive and enabling them to build better data products.
• Bonus points for experience with tools like Databricks, Spark, dbt, Looker, or DataHub, and interest in exploring AI-assisted analytics or developer productivity tooling.

Experience is great, but we also look for drive, intelligence, and integrity. So, even if you don’t tick every box, please consider applying if you feel you’re the kind of person described above!

About the role:

We're looking for a Principal Data Scientist to own Readdle's company-wide data science roadmap and drive measurable business impact across the organization.

This is a role for a hands-on technical leader with a business mindset — someone who sets methodological standards, prototypes and productionizes predictive and prescriptive systems, and serves as the internal authority on machine learning, autonomous systems, experimentation, causal inference, optimization, and advanced analytics.

You'll work closely with Product, Engineering, Marketing, Data Platform, and Analytics to embed data-driven decision-making into how we build and grow.

What you will do:

• Own the Data Science roadmap and its technical architecture across the company, ensuring focus on the highest-leverage opportunities and scalable foundations.
• Hands-on build and productionize DS models end-to-end: from hypothesis → prototype → reliable production systems that optimize the proper business metrics.
• Methodological excellence: create, maintain, ensure adoption, and evolve advanced analytics frameworks and enablement cross-functionally, including:
• experimentation design and analysis
• causal inference and incrementality testing (incl. diff-in-diff, synthetic control, uplift, geo experiments, incrementality, etc.)
• measurement frameworks and proxy metric design
• optimization & prescriptive analytics
• Inference in marketing measurement (incl. MMM and Bayesian measurement where applicable)
• Develop predictive and prescriptive capabilities, including revenue & churn prediction, time-series forecasting, anomaly detection, and decision-optimization systems.
• Define and defend proxy measurements when direct measurement is infeasible; select the right method for the task and clearly articulate assumptions/tradeoffs.
• Partner with Data Platform & Analytics teams to jointly ensure high-quality, well-modeled, accessible SSOT data for data science;
• Act as the technical bridge between Product, Engineering, and Marketing to ensure data science is embedded in product lifecycle decisions (discovery, rollout, iteration).
• Own & drive standards around DS reproducibility, testing, CI/CD, version control, packaging, documentation, and monitoring.
• Mentor Senior Data Scientists; create learning paths, review work for methodological rigor, and build a culture of technical excellence.

About you:

• Proven experience as a Principal / Staff Data Scientist (or equivalent) delivering cross-functional, company-level impact and setting technical direction.
• Deep expertise in advanced analytics and measurement, including strong proficiency in:
• experimentation and causal inference
• incrementality measurement, optimization / prescriptive analytics
• defining proxy metrics and causal graphs
• Strong track record of building and productionizing ML systems (predictive and/or prescriptive), including:
• time series forecasting and anomaly detection
• causal graphs / structural thinking (when appropriate)
• MMM and/or marketing measurement approaches (as applicable to the business)
• Deep Python expertise plus at least one library in each category:
• ML/DL: (e.g., scikit-learn, XGBoost/LightGBM, PyTorch, TensorFlow)
• Statistics: (e.g., statsmodels, SciPy, etc.)
• Causal inference: (e.g., DoWhy, EconML, CausalML, causalimpact, PyWhy)
• Strong engineering and MLOps fundamentals, including experience with:
• Python in production, containers, and distributed computing
• CI/CD, testing, version control, reproducibility best practices
• modern data modeling frameworks (e.g., dbt/dataform), orchestration patterns, and model monitoring
• AI developer productivity tools and strong craftsmanship
• Excellent business acumen, stakeholder management, and communication: ability to translate complex methods into clear decisions, assumptions, and tradeoffs for senior leaders.
• Ability to operate across ambiguity, prioritize ruthlessly, and deliver outcomes with high standards of rigor.

Your key skills and capabilities: 

• Strong SQL and Python skills  

• Data modelling experience (dimensional, relational, or similar)  

• Experience building and maintaining backend systems  

• Familiarity with Microsoft Azure  

• Understanding of APIs, containers, and backend development best practices 

• Implementing cloud-native data platforms 

• Engineering scalable and reliable pipelines 

• Good knowledge of distributed computing with Spark 

• Understanding of cloud architecture principles and best practices 

• Hands-on experience in designing, deploying, and managing cloud resources 

• Agile ways of working 

• Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform 

• Monitoring and performance tuning of cloud-based applications and services  

Nice to haves:  

• Experience with Snowflake, dbt, CubeJS 

• Experience with Databricks, PySpark, ML workflows  

• Experience with containerized deployments (Docker, Kubernetes, Azure Container Apps).  

• Frontend development experience (React, Next.js, TypeScript)  

• Infrastructure-as-code (Terraform, CloudFormation) 

• Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance  

• Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining   

• ML Pipelines & CI/CD – Automate end-to-end ML workflows 

Key tasks:  

• Develop, maintain, and optimise backend services for our SaaS platform  

• Work with SQL and Python daily to build robust data pipelines and transformations  

• Model, structure, and query data to support product features and reporting  

• Integrate and maintain data ingestion flows (e.g., Fivetran, custom connectors)  

• Implement backend APIs (FastAPI) to power our web application  

• Work with our cloud environment (Azure - experience with AWS or GCP also valuable)  

• Collaborate with teammates to plan, build, and deploy features in an Agile way 

• Contribute to CI/CD workflows, monitoring, and infrastructure-as-code 

We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform.