Senior Data Engineer

Transcarent is a health and care company providing a generative AI-powered platform for health consumers. The Senior Data Engineer will architect and maintain reliable, scalable data pipelines and cloud-native data platforms, while applying AI/ML to automate data engineering work and enable new analytics capabilities. The role also involves cross-functional partnership, production issue resolution, data quality, modernization, and technical mentorship.

Responsibilities:

• Architect, build, and maintain enterprise - scale data pipelines that process large volumes of data with high reliability and performance
• Own and evolve core components of our cloud - native data platform, built on modern tools such as Databricks and AWS
• Design and implement data integration solutions across internal and third - party systems, ensuring data quality and consistency end to end
• Apply AI/ML - including LLM - based agents and automation - to solve data engineering problems, reduce manual toil, and unlock new analytics capabilities
• Build and optimize data models across our AWS and Databricks environments
• Partner with cross - functional stakeholders to translate business requirements into scalable data solutions
• Implement and enforce data quality controls and observability practices across the pipeline lifecycle
• Diagnose and resolve complex production data issues with minimal oversight
• Mentor other engineers on the team, raising the technical bar for code quality, architecture, and operational excellence
• Research and evaluate emerging tools and techniques (AI, data platform, orchestration) and recommend adoption where it drives impact
• Other duties as assigned

Requirements:

• • BS or MS in Computer Science, Data Science, or related field (or equivalent practical experience)
• • 5+ years of professional data engineering experience, with demonstrated technical leadership
• • Expert - level proficiency in Python and SQL, including experience building enterprise - scale data processing applications and optimizing complex queries
• • Advanced hands - on experience with Databricks (or similar platforms) and AWS data services (e.g., S3, Redshift, RDS, Glue, Lambda)
• • Proven track record designing and implementing large - scale data warehousing solutions and complex ETL/ELT pipelines
• • Experience with modern orchestration frameworks such as Airflow
• • Strong grounding in data modeling and dimensional modeling best practices
• • Demonstrated interest or experience applying AI/ML to data engineering problems (automation, agents, anomaly detection, or similar)
• • Experience working in Agile environments with CI/CD practices
• • Excellent written and verbal communication skills; ability to explain technical tradeoffs to both engineers and business stakeholders
• • Comfort operating independently in a fast - paced, evolving environment
• • Experience with dbt or data observability/quality tooling
• • Experience with customer engagement or communications platforms
• • Experience in healthcare, benefits, or health tech
• • Experience building or integrating LLM - powered agents or AI - driven tooling into production data systems
• • Experience leading migrations of legacy data infrastructure to modern cloud - native platforms
• • Experience mentoring or informally leading other engineers