Role OverviewWe are looking for a Senior Data Engineer to design and build scalable data lakes, warehouses, and lakehouse architectures supporting a thematic research platform that processes large volumes of financial data daily.
What You Will Do
- Design and implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ingestion workflows from third-party APIs, and work with Snowflake, Spark, and AWS to deliver high-performance data infrastructure.
Why It Might Be a Fit
The role combines hands-on engineering with technical consulting responsibilities, translating business goals into data architecture roadmaps.
Requirements
- Authorized to work for ANY employer in the US
- Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience
- 5+ years of experience with Python
- 5+ years of experience with data processing, manipulation, and analytics libraries like Pandas, Polars, PySpark or DuckDB
- 2+ years of experience with Big Data technologies (Spark, Snowflake)
- Expert-level knowledge of pipeline orchestration using Airflow or similar industry-standard tools
- Deep understanding of Medallion Architecture, columnar file formats, and diverse database technologies (SQL, NoSQL, and Lakehouse architectures)
- Proven ability to work with 3rd party APIs for complex data ingestion tasks
- Proficiency with modern Cloud platforms (AWS, GCP, Snowflake) and advanced SQL optimization
- Exceptional soft skills with a proven ability to gather requirements from leadership and collaborate effectively across cross-functional teams
- Upper-intermediate English level
Benefits
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets
- Exciting projects: Modern solutions with Fortune 500 and top product companies
- Flextime: Flexible schedule with remote and office options
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