Senior Data Engineer
Skills
- Expertise in SQL and Python programming.
- Hands-on experience with Snowflake (or Redshift/BigQuery) and DBT.
- Knowledge of orchestration tools like Airflow and infrastructure automation tools such as Terraform.
- Familiarity with CI/CD pipelines and Docker.
- Experience in dimensional modeling, CDC, ELT best practices, and API/event stream integration.
- Strong data-quality and pipeline reliability frameworks.
- Excellent written and verbal communication skills.
Responsibilities
- Design and maintain scalable data models and schemas in DBT and Snowflake to support analytical and operational workloads.
- Build, optimize, and document ELT pipelines using SQL, Python, and dbt for batch and near-real-time data ingestion.
- Implement automated data-quality testing, monitoring, and alerting frameworks.
- Collaborate with Product and Engineering teams on event instrumentation, schema design, and data governance.
- Tune data warehouse performance and manage costs through partitioning, clustering, and workload management.
- Partner with Analytics and Data Science teams to translate business questions into engineered data solutions.
- Mentor junior engineers and analysts promoting best practices in coding, documentation, and peer review.
Education
- Bachelor’s degree in Computer Science, Data Engineering, or related field preferred.
Benefits
- Competitive annual compensation between $160,000 and $200,000.
- Equity grant participation eligibility for new hires.
- Comprehensive and affordable healthcare insurance plans.
- 401(k) with employer match and access to retirement advisors.
- Paid parental leave and family planning reimbursement programs.
- Sponsored learning and development programs for professional growth.
- Fully stocked kitchen and lunch reimbursement.
- Hybrid work model with in-office and work-from-home flexibility.
- Generous paid time off (PTO).
Average salary estimate
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