Data Engineer

About the Role

Join our Data Platform & Analytics team and help shape the trusted data foundation that powers analytics, strategy, and downstream applications. As a Senior Data Engineer, you will independently own the design and operation of scalable data pipelines and platform capabilities across our Snowflake and AWS environment. You will solve complex, cross-functional data problems, exercise strong technical judgment, and partner across the organization to make data reliable, accessible, and ready for a growing set of business and technical use cases.

What You'll Do

• Design, development, and operate reliable data pipelines for first-party and third-party data across batch, streaming, and change data capture (CDC) patterns.
• Lead the technical design of ETL/ELT and orchestration workflows, selecting appropriate patterns and tradeoffs for performance, scalability, maintainability, and cost.
• Develop high-quality SQL and Python solutions for transformation, validation, automation, and complex data processing, while setting a strong standard for maintainable engineering practices.
• Design and strengthen data quality, freshness monitoring, alerting, and observability so issues are detected and resolved before they materially impact downstream users.
• Optimize Snowflake workloads, storage, and pipeline architecture with attention to reliability, scalability, platform performance, and cost efficiency.
• Lead investigation of complex production data incidents, identify root causes across systems, and implement durable fixes that improve platform resilience and reduce recurrence.
• Partner with Analytics Engineering, Data Science, Product, Engineering, and other technical stakeholders to evaluate source systems, define dependable data contracts, and deliver data products that support analytics and downstream applications.
• Drive and evolve engineering standards and reusable patterns across automated testing, version control, CI/CD, documentation, schema design, and pipeline development; provide technical guidance and code review to other engineers when appropriate.

Requirements

• 5+ years of Data Engineering or closely related experience designing, building, and operating production data systems; bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Advanced SQL skills and strong proficiency in Python or a similar programming language for data processing, automation, and production engineering.
• Strong experience with a modern cloud data warehouse such as Snowflake and cloud infrastructure such as AWS, including performance, reliability, and cost considerations.
• Deep experience with ETL/ELT, orchestration, schema design, and data modeling using tools such as dbt, Airflow, or similar technologies.
• Strong understanding of batch and real-time data architectures, including streaming and change data capture (CDC) technologies and their operational tradeoffs.
• Demonstrated experience designing data quality controls, testing frameworks, monitoring, observability, and production support practices for critical data pipelines.
• Strong working knowledge of Git-based development, CI/CD, automated testing, and modern software engineering practices for data systems.
• Demonstrated ability to independently solve complex and ambiguous technical problems, exercise sound judgment, and communicate tradeoffs and recommendations to senior technical and business stakeholders.

Benefits and Perks

• 100% company-paid medical, dental, and vision coverage for you and your dependents on your first day of employment.
• Receive up to $100 per month in fitness reimbursement or enjoy a complimentary full membership to LifeTime Fitness or Equinox.
• 401(k) with a 3.5% match and immediate vesting.
• Meal program available for both lunch and dinner.
• Pre-tax benefits, including a $1,000 HSA match.
• Life and accidental insurance.
• Flexible PTO.