Senior Data Engineer
| Company | Maven Clinic |
|---|---|
| Location | Remote in USA, New York, NY, USA |
| Salary | $196000 – $230000 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s |
| Experience Level | Senior |
Requirements
- Bachelor’s or Master’s degree in Computer Science or related field, or equivalent experience.
- 6+ years of experience in data engineering or backend systems development, with a track record of building scalable, performant, and reliable data solutions.
- Highly proficient in SQL or similar languages for data transformation / ETL and analysis.
- Deep experience in data modeling for large-scale distributed data warehouses (e.g., BigQuery, Redshift, Snowflake), with a strong understanding of design trade-offs and best practices.
- Demonstrated ability to collaborate effectively with cross-functional partners, particularly product, analytics, and operations teams.
- Working proficiency in one of the programming languages (Java, Python, Go, etc.), and hand-on experience with one of the workflow orchestration tools (eg. Apache Airflow)
- Product-oriented mindset with a strong focus on scalable, maintainable engineering solutions that meet real business needs.
- Experience leading design reviews and setting engineering standards and architecture direction.
- Strong problem-solving abilities, with a bias for action and a drive to deliver high-quality solutions in a fast-paced environment.
Responsibilities
- Lead the design, development, and maintenance of high-performance, cost-efficient data pipelines – both batch and streaming.
- Build and maintain robust data ingestion and export workflows that ensure end-to-end data quality, observability, and reliability in production environments.
- Collaborate with data platform and backend engineering teams to evolve a scalable, secure, and fault-tolerant data architecture.
- Drive technical design reviews and provide mentorship on engineering best practices, data architecture principles, and high coding standards.
- Partner with product and service engineering teams to shape and model source datasets, ensuring alignment with a unified data vision across systems.
- Stay ahead of emerging technologies, frameworks, and trends in the data space to inform architectural decisions and drive innovation within the team.
Preferred Qualifications
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No preferred qualifications provided.