Principal Data Engineer

Gainwell Technologies LLC • OH

140d • $113,700 - $162,400

About The Position

Gainwell Technologies is seeking a highly experienced Principal Data Engineer to lead the design, development, and optimization of large-scale data solutions across our healthcare technology platforms. This role focuses on architecting modern data pipelines, building scalable data platforms, and enabling advanced analytics and AI/ML capabilities while ensuring data integrity, security, and compliance with healthcare industry regulations.

Requirements

• 15+ years of experience in data engineering and data platform development, preferably in healthcare or regulated industries.
• Proven expertise with big data technologies (Apache Spark, Hadoop, Kafka, Flink) and modern data stacks.
• Strong skills in SQL, Python, and/or Scala for data engineering and pipeline development.
• Hands-on experience with cloud-native data platforms (AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow, or Snowflake).
• Deep understanding of data modeling (relational, dimensional, NoSQL) and modern storage architectures (data lakes, warehouses, lakehouses).
• Strong grasp of data security, compliance frameworks, and healthcare data standards (HL7, FHIR, HIPAA).

Responsibilities

• Design, build, and optimize robust, scalable, and high-performance data pipelines and workflows for structured, semi-structured, and unstructured healthcare datasets.
• Architect and implement modern data platforms in AWS, Azure, or GCP using services such as Databricks, Snowflake, Redshift, BigQuery, or Synapse.
• Develop and manage ETL/ELT workflows using tools like Apache Spark, Airflow, dbt, Informatica, or Talend.
• Integrate data from diverse sources (EHRs, claims, IoT, APIs, flat files, databases) into unified data platforms, ensuring high reliability and low latency.
• Ensure adherence to HIPAA, CMS, and other regulatory standards, with strong focus on data quality, lineage, cataloging, metadata management, and governance frameworks.
• Continuously tune data pipelines and queries for scale, speed, and cost efficiency, leveraging distributed systems and modern storage formats (Parquet, ORC, Delta).
• Implement DataOps best practices for CI/CD, observability, version control, and automated testing of data pipelines.
• Partner with data scientists and AI engineers to provision curated, high-quality datasets, feature stores, and real-time data pipelines for advanced analytics and AI/ML workloads.
• Skilled in SQL, NoSQL, graph databases, and data lakes/lakehouses, including optimization and partitioning strategies.
• Implement robust data encryption, access control, and guardrails for secure and compliant data handling.
• Lead cross-functional data engineering initiatives, mentor team members, and collaborate with technology and business leaders to deliver strategic data solutions.

Benefits

• Generous, flexible vacation policy
• 401(k) employer match
• Comprehensive health benefits
• Educational assistance
• Leadership and technical development academies

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 5,001-10,000 employees