Software/DevOps Engineer

Software development (~45–55%) Design, develop, and maintain backend services and supporting applications. Build and enhance data ingestion components, including integrations, transformations, and validation logic. Partner with teammates to debug and resolve production issues with a strong focus on root‑cause analysis and long‑term fixes. Develop internal tools and automation to reduce friction and improve reliability. Collaborate with product and data teams to ensure solutions are production‑ready and operationally sound. Product data operations (~20%) Own and execute recurring product data ingestion cycles. Monitor ingestion runs, manage retries, and address failures or partial loads. Validate data completeness, timeliness, and basic quality checks. Coordinate with product, analytics, and support teams when ingestion issues impact downstream workflows. Perform root‑cause analysis on ingestion failures and implement improvements to prevent recurrence. DevOps, release, and runtime operations (~25–30%) Maintain and improve CI/CD pipelines supporting application deployments. Coordinate application releases with engineering teammates to deliver changes safely and reliably. Monitor application health, logs, and alerts; respond to incidents and production issues to maintain reliable, high-performing services Manage environment configuration and secrets in alignment with security best practices. Participate in incident response and contribute to post‑incident reviews. Improve operational guardrails such as retries, timeouts, monitoring, and alerting. Collaboration & leadership Work closely with architecture, engineering, product, data, and support teams in a highly collaborative environment. Provide technical guidance on platform resilience best practices and production readiness. Contribute to improving processes, documentation, and operational clarity across teams. Support data security and compliance efforts in coordination with engineering leadership. Continuous improvement Identify opportunities to reduce manual operational work through pragmatic automation. Improve reliability and observability based on real production experience. Look for opportunities to simplify work, improve reliability, and help teammates deliver software more efficiently. The skills and experience you bring to this role include: Bachelor’s degree in computer science, Informatics, Information Systems, or another quantitative field. 10+ years of experience in data engineering or a similar role with demonstrated technical leadership experience. Expertise building and administering, including writing views, stored procedures, and triggers, in AWS-native data systems (Redshift, Aurora, RDS PostgreSQL, Glue, Lambda, Step Functions, MWAA-Airflow). Strong Python and SQL experience, including advanced query design and database optimization. Experience with healthcare data (Medical Claims, Rx Claims) or similar healthcare data is required. Ability to develop subject-matter expertise and partner thoughtfully with business teams. Trusted partner: reliable to deliver accurate work in a timely manner. A passion for working with a team to improve how data drives meaningful outcomes.