Arine is a rapidly growing healthcare technology and clinical services company focused on improving medication management and patient care through innovative software solutions. The Data Engineering Lead will oversee a team of Data Engineers to ensure the delivery of high-quality data pipelines while maintaining existing systems, as well as managing project timelines and team performance.
Responsibilities:
- Collaborate with the Implementation team and Data Analyst to review and own DE requirement writeups, ensuring they fully address data needs discussed in implementation calls
- Communicate timelines for deliverables to unblock Data Engineers for ETL pipeline development
- Proactively flag risks to timelines or quality to stakeholders and project managers
- Lead backlog grooming for implementation-related tickets
- Ensure team cross-coverage by making sure the DE Lead and assigned Data Engineer understand the full ETL flow, with at least two additional engineers familiar at a high level
- Conduct thorough peer reviews and DE UATs after initial UAT completion
- Design and maintain data transformation pipelines using dbt, including macros, incremental models, and dbt tests
- Work with QA and CSA teams to resolve post-UAT issues and update the DE UAT checklist
- Provide technical guidance and mentorship to junior engineers, and promote best practices and coding standards
- Identify and escalate inefficiencies within and across teams
- Support project management and provide leadership to peers as needed
- Author and support high-quality technical documentation, assisting junior engineers in doing the same
- Collaborate with the DE Manager to report on DE contractor performance issues
Requirements:
- 6+ years working with data in production environments
- Proven ability to lead a small team (up to 3 engineers)
- Track record of building automated ETL workflows using Python and dbt SQL
- Hands-on proficiency with modern data technologies and comfort leveraging AI coding assistants to accelerate development, improve code quality, and enhance productivity
- Strong skills in data processing, validation, cleaning, and debugging across complex datasets
- Demonstrated success building production-grade dbt pipelines (macros, incremental and Python models, and testing)
- Deep, demonstrable understanding of healthcare and healthcare claims data
- Comfort working with large-scale datasets (10GB+)
- Excellent verbal and written communication skills
- Ability to pass a background check
- Must live in and be eligible to work in the United States
- Familiarity with AWS services such as S3, DynamoDB, Batch, and Step Functions
- Hands-on knowledge of Snowflake
- Strong data modeling skills for reporting and business intelligence solutions