Data Engineer - Healthcare

Compunnel, Inc.; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Compunnel, Inc. seeks a skilled Data Engineer to design, develop, and optimize scalable pipelines and platforms supporting analytics, AI/ML, and healthcare operations.

The role emphasizes cloud-based ETL/ELT development, big data tech, data quality, and governance while collaborating with analysts, architects, and data scientists to meet enterprise data requirements.

Qualifications

• Experience in data engineering and building scalable data pipelines.
• Experience with ETL/ELT design and development.
• Proficiency in data warehousing concepts and data modeling.
• Strong understanding of data lake architectures.
• Experience with cloud platforms (AWS or Azure).
• Proficiency with SQL databases (SQL Server, Oracle, PostgreSQL, Snowflake).
• Proficiency with Python, SQL, PySpark, and shell scripting.
• Experience with Spark/Hadoop ecosystem.
• Familiarity with DevOps and CI/CD practices (Git, Jenkins, Azure DevOps).

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data ingestion frameworks from multiple source systems, APIs, databases, and cloud platforms.
• Develop and maintain enterprise data models, data warehouses, and data lakes.
• Ensure high levels of data quality, integrity, security, and governance across data platforms.
• Collaborate with business analysts, architects, data scientists, and application teams to understand data requirements.
• Implement data transformation, validation, reconciliation, and monitoring processes.
• Optimize performance of large-scale data pipelines and database workloads.
• Support analytics, reporting, AI/ML, and advanced data science initiatives through reliable data delivery.
• Implement metadata management, lineage tracking, and data cataloging solutions.
• Troubleshoot production issues and perform root cause analysis for data-related incidents.
• Participate in code reviews, architecture discussions, and technical design sessions.
• Ensure adherence to healthcare regulatory and compliance requirements, including HIPAA and data privacy standards.
• Work with distributed teams across multiple locations and support enterprise-scale data initiatives.

Skills

Data Engineering

Data Pipeline Development

ETL/ELT Design and Development

Data Warehousing Concepts

Data Modeling

Data Lake Architecture

Data Quality and Data Governance

Cloud Technologies (AWS/Azure)

Databases (SQL Server, Oracle, Postgre

Python

SQL

PySpark

Shell Scripting

Big Data Technologies (Spark, Hadoop)

DevOps & CI/CD (Git, Jenkins/Azure Dev

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field

Tools

AWS

Azure

Databricks

Snowflake

Job description

JOB SUMMARY

We are seeking a skilled Data Engineer to design, develop, and optimize scalable data pipelines and data platforms that support enterprise analytics, reporting, AI/ML initiatives, and healthcare business operations. The ideal candidate will have strong expertise in cloud-based data engineering, ETL/ELT development, big data technologies, and data quality practices, with experience working in healthcare environments.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data ingestion frameworks from multiple source systems, APIs, databases, and cloud platforms.
• Develop and maintain enterprise data models, data warehouses, and data lakes.
• Ensure high levels of data quality, integrity, security, and governance across data platforms.
• Collaborate with business analysts, architects, data scientists, and application teams to understand data requirements.
• Implement data transformation, validation, reconciliation, and monitoring processes.
• Optimize performance of large-scale data pipelines and database workloads.
• Support analytics, reporting, AI/ML, and advanced data science initiatives through reliable data delivery.
• Implement metadata management, lineage tracking, and data cataloging solutions.
• Troubleshoot production issues and perform root cause analysis for data-related incidents.
• Participate in code reviews, architecture discussions, and technical design sessions.
• Ensure adherence to healthcare regulatory and compliance requirements, including HIPAA and data privacy standards.
• Work with distributed teams across multiple locations and support enterprise-scale data initiatives.

Required Qualifications

• Data Engineering
• Data Pipeline Development
• ETL/ELT Design and DevelopmentData Warehousing Concepts
• Data Modeling (Dimensional & Relational)
• Data Lake Architecture
• Data Quality and Data Governance
• Cloud Technologies AWS (Glue, EMR, Lambda, S3, Redshift, Athena) or Azure (ADF, Data Lake, Synapse, Databricks)
• Databases SQL Server Oracle PostgreSQL Snowflake
• Programming Python SQL PySpark Shell Scripting
• Big Data Technologies Apache Spark Hadoop Ecosystem
• DevOps & CI/CD Git Jenkins/Azure DevOps CI/CD Pipeline Implementation

Preferred Qualifications

• Experience in Healthcare, Health Insurance, or Life Sciences domain.
• Exposure to AI/ML data pipelines and MLOps frameworks.
• Knowledge of healthcare data standards such as HL7, FHIR, ICD, and CPT is preferred.
• Experience with Snowflake, Databricks, or modern cloud-native data platforms.
• Familiarity with Agile/Scrum methodology.
• Education Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.

Certifications

None