Senior Data Engineer, Progyny

• Strong communication skills
• Experience with well-known data pipeline/transform tools / platforms (DAG-based options like Airflow, Dagster, Prefect, etc.)
• 7+ years of consistent, professional SQL development experience
• 5+ years of Python development experience
• Experience with data access patterns (caching, partitioning, sharding)
• Familiarity with data modeling best practices / data structures/ data warehousing

Desirable

• This role will directly support all Machine Learning and AI based solutions at Progyny
• This role will be directly responsible for supporting Progyny’s efforts to provide an enhanced member experience and better insights to our team leveraging best in class components for core data persistence, streaming, transformation, and integrated analytics leveraging machine learning
• As data systems are constantly evolving, this role will also be expected to help challenge and mature the existing patterns, practices and tool chains for the Data engineering discipline at Progyny; as such, a successful candidates should be motivated by a desire to help optimize and shape their environment, not simply follow the established status quo
• Working with machine learning and AI stakeholders to design and implement numerous data transformation pipelines, with a focus on all functional/non-functional quality goals
• Design and implementation of test, monitoring, and observability strategies for data systems and processes
• Support for outage incident response and return-to-service activities for data systems in your purview
• Supporting evaluation of related tools, frameworks and dev/test/deploy patterns as needed to evolve the platform capabilities for data support