Senior Data Engineer
$119,700–$199,300 year
On-site · Washington, District of Columbia, United States
Job Summary
Senior Data Engineer at The Washington Post leading data engineering efforts for AI-powered projects, building scalable data pipelines using Python, PySpark, Spark, and Flink to support Generative AI, personalization, and recommendation systems, while collaborating with data scientists, product managers, and designers to deliver high-quality, scalable data solutions. Responsibilities include gathering requirements, writing and deploying code, reviewing and mentoring junior engineers, and ensuring secure, observable data pipelines; the role involves cross-functional collaboration across engineering, product, design, and newsroom teams, with on-site work five days a week in Washington, DC, and a salary range of $119,700–$199,300 annually.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, or a related field (Master's preferred)
- 3+ years of experience in ETL/ELT, data modeling, and querying large datasets using SQL
- Experience with Python and PySpark for ETL development
- Experience with AWS Data Lakehouse technologies (Redshift, Athena, EMR, Glue catalog)
- Strong understanding of Pub/Sub and event-driven architecture
- Ability to design and deploy DAGs using Apache Airflow
- Experience with Apache Iceberg, Postgres, MySQL, DynamoDB, Tableau, and Superset; Ad Tech data familiarity
- Cloud infrastructure proficiency with AWS services (EC2, S3, RDS, Lambda, Batch) and containerization with Docker/ECS
- Experience with CI/CD, testing, code reviews, and scalable software development practices
- Mentorship/leadership experience; ability to communicate with technical and non-technical stakeholders
- Strong problem-solving and autonomous project management skills
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