Senior Data Engineer
Build and scale data pipelines, reusable datasets, and validation frameworks supporting business intelligence, marketing, and data science. The role requires strong Python and SQL skills, modern data-stack experience, and at least four years of software or data engineering experience.
About the job
Responsibilities
- Build, optimize, and maintain data pipelines that power the business.
- Define and build reusable, abstracted datasets for Business Intelligence, Marketing, and Data Science Research.
- Design, build, and promote federated data-validation frameworks to monitor potential data inconsistencies.
- Protect user privacy and security through best practices.
Requirements
- 4+ years of software or data engineering experience, including distributed data processing, data warehousing, data governance, Big Data, data variance, data privacy, and data quality.
- Strong Python and SQL experience.
- Experience building scalable data pipelines, optimizing queries, modeling data, and defining reusable datasets.
- Experience with orchestration tools, especially Airflow; databases, especially PostgreSQL; data lakes, especially Iceberg; and data warehouses, especially Snowflake.
- Experience with SQL tuning, Spark development, medallion architectures, and event-driven architectures.
- Familiarity with healthcare or insurance.
- Familiarity with data security and HIPAA compliance.
Technologies
- Postgres/SQL
- Snowflake
- Python
- AWS
- Terraform
- Argo
- Airflow
- Spark
- DuckDB
- Iceberg
- Airbyte
- dbt
- Elasticsearch/OpenSearch
- OpenTelemetry
- Looker
Compensation and Benefits
- Target salary range: $220,000–$245,000 annually.
- Eligible for equity incentives and benefits including flexible paid time off, medical/dental/vision plans, 401(k) with company match, flexible spending accounts, and Teladoc Health.
Skills
Python, SQL, AWS, Apache Airflow, Postgres, Apache Iceberg, Snowflake, Spark, Terraform, dbt, Duckdb, Airbyte, Elasticsearch, HIPAA
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