Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Stream Compute team at Stripe builds and operates the infrastructure, tooling, and systems behind our Flink-powered stream processing systems. We're at the heart of several core asynchronous workflows, operating at significant scale and handling vast amounts of sensitive financial data. Our work powers intricate processes involving various critical financial operations and real-time analytics. We run globally distributed systems with high reliability and performance to meet Stripe's scaling, availability, and product needs, and we continually reduce operational toil by investing in automation and self-service tooling for upgrades, maintenance, and day-to-day operations. The team is distributed between Seattle, Toronto and remote locations.

What makes our team truly exciting is our commitment to our users: we ensure no event is dropped, state integrity is preserved, and support exactly-once processing as a first-class feature. Working at the intersection of real-time data processing and fintech innovation, we continuously push the boundaries of what's possible. Our focus on innovation, user experience, reliability, and compliance drives increased ROI and operational excellence, making us a crucial part of Stripe's success.

What you'll do

You'll help define and deliver the next generation of Stripe's Flink-first stream compute infrastructure—driving innovation to meet extremely high availability targets at global scale. Partnering with infrastructure engineers, adjacent platform teams, and the product orgs that depend on Flink every day, you'll set a long-term technical direction that scales with Stripe's growth while enabling reliable, efficient operations for years to come. You'll work on the hardest problems in operating Flink in production—state management, exactly-once processing, performance isolation, and automated recovery—so teams across Stripe can confidently build stateful stream processing applications on top of it.

Responsibilities

• Design, build, and operate stream compute infrastructure with Apache Flink at the center, alongside technologies like Kafka, Temporal, and AWS services
• Partner with product and platform teams across Stripe to understand requirements, unblock Flink adoption, and improve how stream processing infrastructure is used end-to-end
• Define and implement operational best practices (e.g., shuffle sharding, cellular architecture, load shedding, automated state recovery) to improve resilience and reliability at scale
• Drive fleet-level automation and standardization ("pets" to "cattle") through self-service workflows, safer rollouts, and self-healing systems that reduce manual operations
• Lead initiatives that raise the bar on Flink availability and state durability (e.g., multi-region strategies, disaster recovery readiness, operational readiness reviews, incident learning)
• Evaluate and productionize Flink ecosystem capabilities (e.g., SQL, connectors, state backends) to improve developer experience and scalability without compromising reliability
• Work closely with the open source community to identify opportunities for adopting new open source features as well as contribute back to OSS

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• This is a Staff-level role - that typically means 10+ years of experience building, operating, and evolving large-scale production systems
• Experience as a technical lead for team(s) working on distributed systems, including scaling them in fast-moving environments
• Hands-on experience with big data technologies such as Flink, Spark, Kafka, Pulsar, or Pinot
• Experience developing, maintaining and debugging distributed systems built with open source tools
• Experience building and scaling infrastructure as a product
• Strong software engineering skills and a passion for Big Data Distributed Systems
• Ability to write high quality code (in programming languages like Go, Java, Scala, etc)
• Comfortable operating with high autonomy and ownership
• Growth mindset and a willingness to learn quickly, explore ambiguous problem spaces, and dive deep when needed
• Strong written and verbal communication skills, including the ability to produce clear technical documentation

Preferred qualifications

• Experience operating streaming infrastructure as a platform (e.g., Flink clusters, Kafka, Pulsar) for internal customers at scale
• Deep hands-on experience authoring, optimizing, and operating real-time processing frameworks such as Flink, Spark Streaming, Storm, or Kafka Streams in production
• Experience building or operating control planes for managing large-scale infrastructure
• Open source contributions to data processing or big data systems (Hadoop, Spark, Celeborn, Flink, etc)

Who We Are

Konrad is a next generation digital consultancy. We are dedicated to solving complex business problems for our global clients with creative and forward-thinking solutions. Our employees enjoy a culture built on innovation and a commitment to creating best-in-class digital products in use by hundreds of millions of consumers around the world. We hire exceptionally smart, analytical, and hard working people who are lifelong learners.

About The Role

As a Senior Data Engineer you’ll be tasked with designing, building, and maintaining scalable data platforms and pipelines. Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure reliable, secure, and efficient data solutions.

What You’ll Do

• Design, build, and manage robust data pipelines and data architectures.
• Implement solutions leveraging platforms such as Azure Fabric, Databricks, and Snowflake.
• Optimize data workflows, ensuring reliability, scalability, and performance.
• Collaborate with internal stakeholders to understand data needs and deliver tailored solutions.
• Ensure data security and compliance with industry standards and best practices.
• Perform data modelling, data extraction, transformation, and loading (ETL/ELT).
• Identify and recommend innovative solutions to enhance data quality and analytics capabilities.

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Engineering, Information Technology, or a related field.
• 4+ years of professional experience as a Data Engineer or similar role.
• Proficiency in data platforms such as Azure Fabric, Databricks, and Snowflake.
• Hands-on experience with data pipeline tools, cloud services, and storage solutions.
• Strong programming skills in SQL, Python, or related languages.
• Experience with big data technologies and concepts (Spark, Hadoop, Kafka).
• Excellent analytical, troubleshooting, and problem-solving skills.
• Ability to effectively communicate technical concepts clearly to non-technical stakeholders.

Nice to have

• Certifications related to Azure Data Engineering, Databricks, or Snowflake.
• Familiarity with DevOps practices and CI/CD pipelines.

Perks and Benefits

• Comprehensive Health & Wellness Benefits Package 
• Retirement Planning
• Parental Leave Program
• Annual tech & travel allowance
• Flexible Working Hours
• Work from Home Flexibility
• Service Recognition Programs
• Socials, Outings & Retreats
• Culture of Learning & Development

Bonus Points

Have you taken any courses at BrainStation? A lot of our design and development best practices and processes are taught during our courses - make sure to highlight this experience in your cover letter if you have!

Konrad is committed to maintaining a diverse work environment and is proud to be an equal opportunity employer. All qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status will receive consideration for employment. If you have any accessibility requirements or concerns regarding the hiring process or employment with us, please notify us so we can provide suitable accommodation.

The estimated compensation for this position is $120,000 to $145,000. This is an estimate and a compensation offer will vary based on applicant’s education, experience, skills, abilities and alignment with market data.

While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted.

#LI-Hybrid

About the Role:

We are seeking an experienced Principal Software Engineer (Data) to join our fast-paced, collaborative data team. In this role, you will have broad authority to drive the direction of our technographic data services, building world-class data pipelines and systems to process billions of signals and data points. This is an exciting opportunity to solve challenging problems and make a big impact as we invest in making technographics a first-class offering.

What You'll Do:

• Build and optimize big data pipelines to extract and process signals from the web, job postings, and other sources
• Design and implement data architectures and storage solutions to efficiently handle massive data volumes
• Collaborate closely with data scientists to support and integrate ML models into data workflows
• Continuously improve data quality, performance, and scalability of our technographic data platform
• Drive technical strategy and roadmap for the data processing infrastructure.

What We're Looking For:

• Extensive experience building and scaling big data pipelines and architectures from scratch
• Deep expertise in big data frameworks (Hadoop, Spark) and the JVM stack (Java, Scala)
• Strong software engineering fundamentals and ability to write efficient, high-quality code
• Experience with entity recognition and NLP techniques a plus
• Proven track record delivering results and driving projects in a fast-paced environment
• Excellent collaboration and communication skills to work with data scientists, analysts and product teams
• Passion for leveraging huge datasets to power valuable insights.

Ideal Background:

• 10+ years of experience in software engineering roles.
• Experience working with very large datasets and distributed systems
• Familiarity building data pipelines at large tech companies or data-driven organizations
• Bachelor's or advanced degree in Computer Science, Engineering or related technical field.

#LI-SK1

#LI-Remote

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. 

The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. 

As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. 

Responsibilities:

• Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft
• Evolve data model and data schema based on business and engineering needs
• Implement systems tracking data quality and consistency
• Develop tools supporting self-service data pipeline management (ETL)
• SQL and MapReduce job tuning to improve data processing performance
• Write well-crafted, well-tested, readable, maintainable code
• Participate in code reviews to ensure code quality and distribute knowledge
• Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions

Experience:

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• 4+ years of professional experience in data engineering, ideally with large-scale distributed systems.
• Strong skills in Spark, Python (or similar scripting language), and SQL performance tuning
• Experience with AWS, Hadoop/S3, Hive, Presto, Airflow, and related tools
• Solid understanding of ETL processes, workflow orchestration, and data warehousing
• A collaborative mindset—you’re comfortable working across teams to solve real-world problems

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems 

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• M.S. or PhD in Machine Learning or related areas
• Expertise in scalable realtime systems that process stream data
• Passion for applied ML and the Pinterest product

Nice To Have:

• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement: 

•  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration 1-2 times per quarter and therefore needs to be in a commutable distance from the Toronto office (85 Richmond St. W).

#LI-REMOTE

Who We Are

Konrad is a next generation digital consultancy. We are dedicated to solving complex business problems for our global clients with creative and forward-thinking solutions. Our employees enjoy a culture built on innovation and a commitment to creating best-in-class digital products in use by hundreds of millions of consumers around the world. We hire exceptionally smart, analytical, and hard working people who are lifelong learners.

About The Role

As a Data Engineer you’ll be tasked with designing, building, and maintaining scalable data platforms and pipelines. Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure reliable, secure, and efficient data solutions.

What You’ll Do

• Design, build, and manage robust data pipelines and data architectures.
• Implement solutions leveraging platforms such as Azure Fabric, Databricks, and Snowflake.
• Optimize data workflows, ensuring reliability, scalability, and performance.
• Collaborate with internal stakeholders to understand data needs and deliver tailored solutions.
• Ensure data security and compliance with industry standards and best practices.
• Perform data modelling, data extraction, transformation, and loading (ETL/ELT).
• Identify and recommend innovative solutions to enhance data quality and analytics capabilities.

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Engineering, Information Technology, or a related field.
• At least 3 years of professional experience as a Data Engineer or similar role.
• Proficiency in data platforms such as Azure Fabric, Databricks, and Snowflake.
• Hands-on experience with data pipeline tools, cloud services, and storage solutions.
• Strong programming skills in SQL, Python, or related languages.
• Experience with big data technologies and concepts (Spark, Hadoop, Kafka).
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong understanding of data modeling concepts including medallion architecture, data vault, grain, fact tables, dimensions, and schema design.
• Hands-on experience building and maintaining transformation layers using dbt or similar ELT tools.
• Experience building production-grade data models with optimized performance supporting operational decision-making.
• Experience designing batch and real-time ingestion frameworks with real-time monitoring
• Ability to effectively communicate technical concepts clearly to non-technical stakeholders.

Nice to have

• Certifications related to Azure Data Engineering, Databricks, or Snowflake.
• Familiarity with DevOps practices and CI/CD pipelines.

Perks and Benefits

• Comprehensive Health & Wellness Benefits Package
• Retirement Planning
• Parental Leave Program
• Flexible Working Hours
• Work from Home Flexibility
• Service Recognition Programs
• Socials, Outings & Retreats
• Culture of Learning & Development

Bonus Points

Have you taken any courses at BrainStation? A lot of our design and development best practices and processes are taught during our courses - make sure to highlight this experience in your cover letter if you have!

Konrad is committed to maintaining a diverse work environment and is proud to be an equal opportunity employer. All qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status will receive consideration for employment. If you have any accessibility requirements or concerns regarding the hiring process or employment with us, please notify us so we can provide suitable accommodation.

The estimated compensation for this position is $90,000 to $125,000. This is an estimate and a compensation offer will vary based on applicant’s education, experience, skills, abilities and alignment with market data.

While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted.

#LI-Hybrid

P-225

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in eastern Canada

As a Solutions Architect at Databricks within the Field Engineering org you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge and can drive complex technology discussions which express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customer's needs and build valuable customer engagements and report to the Field Engineering Manager.

The impact you will have:

• You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
• You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
• Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role with expertise in at least one of the following technologies:
• Big data engineering (Ex: Spark, Hadoop, Kafka)
• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
• Fluent in SQL and database technology.
• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
• [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Travel to customers in your region up to 30% of the time.