Engineer, Business Intelligence ETL

Overview

With more than 40 years of experience, Concentra is dedicated to our mission to improve the health of America’s workforce, one patient at a time. With a wide range of services and proactive approaches to care, Concentra colleagues provide exceptional service to employers and exceptional care to their employees.

 

Results-driven Senior Data Engineer with over 7 years of experience designing, developing, and optimizing robust ETL pipelines and large-scale data integration solutions. Adept at transforming complex business requirements into scalable, high-performance data systems that drive actionable insights and support strategic decision-making.

Proven expertise in end-to-end ETL development using modern data tools and technologies, including SQL, Python, Spark, and cloud platforms such as AWS and Azure. Skilled in architecting and maintaining data warehouses, data lakes, and real-time streaming solutions to ensure data quality, reliability, and accessibility across diverse enterprise environments.

Recognized for cross-functional collaboration, mentoring junior engineers, and leading initiatives that enhance data platform performance, reduce processing times, and improve data governance. Committed to delivering high-impact solutions that align with business goals, empower analytics, and support data-driven innovation

Responsibilities

Lead the design, implementation, and optimization of ETL/ELT pipelines for large-scale data ingestion and transformation across cloud and on-premise platforms.

 

Develop, deploy, and maintain SSIS packages to extract, cleanse, and load data from disparate sources, ensuring performance efficiency and data consistency across environments.

 

Write, optimize, and maintain complex stored procedures, functions, and views in SQL to support transformation logic, business rules, and operational reporting needs.

 

Collaborate with business stakeholders and analysts to gather data requirements and deliver scalable data solutions aligned with organizational goals.

 

Build and maintain robust data models, metadata repositories, and data dictionaries to support analytics, self-service BI, and compliance with data governance frameworks.

 

Monitor and troubleshoot data pipelines and ETL processes, ensuring high availability, accuracy, and reliability in mission-critical environments.

 

Lead the modernization of legacy ETL workflows by migrating to modern tools such as Azure Data Factory and AWS Glue.

 

Ensure data security, masking, and compliance with regulations such as HIPAA and HITRUST when working with sensitive healthcare or enterprise datasets.

 

Mentor junior engineers through code reviews, training, and architectural guidance, fostering best practices and knowledge sharing.

 

Qualifications

Education Level: Bachelor’s DegreeMajor: Computer Engineering, Computer ScienceDegree must be from an accredited college or university.Experience in lieu of required education is acceptable: Yes

 

 

• Minimum 10 years' experience as an ETL developer with proven track record of successful project implementation
• Minimum of 6 years' experience in reports and data warehouse development
• ETL/ELT Development: Lead the development of secure and compliant ETL/ELT pipelines for healthcare data using AWS Glue and Azure Data Factory integrating clinical, claims, EHR, and operational datasets from various healthcare systems.
• Programming & Scripting: Strong experience using SQL to transform large-scale healthcare datasets (e.g., HL7, FHIR, CCD/CCR formats) and ensure data accuracy. Used Python and Scala to build automated data validation scripts for PHI/PII masking, quality checks, and HIPAA compliance.
• Data Warehousing & Cloud Platforms: Designed and maintained cloud-based healthcare data warehouses using Snowflake and Azure Synapse Analytics, supporting advanced analytics, population health insights, and value-based care reporting.
• Data Modeling & Architecture: Created healthcare-specific data models including dimensional models, star schemas, and FHIR-based structures, enabling efficient data analysis for regulatory reporting, HEDIS, and risk stratification.
• Cloud Infrastructure & DevOps: Deployed secure, HIPAA-compliant infrastructure using Terraform, CloudFormation, and CI/CD tools like GitHub