Cloud Data Engineer - ETL Pipelines & Data Quality

Magpie Health Analytics, Inc.; Baltimore (MD); On-site; USD 110,000 - 165,000; Full time

Job summary

Magpie Health Analytics, Inc. is seeking a Data Engineer to design, build, and optimize cloud-native data pipelines supporting healthcare clients. You will collaborate with backend and architecture teams to enable analytics, reporting, and decision-making.

Responsibilities include ETL/ELT development, data schemas, data quality checks, and documentation. The role emphasizes scalable, testable code, CI/CD workflows, and staying current with evolving data technologies.

Qualifications

• Bachelor’s degree in computer science, engineering, statistics, or related field.
• 4+ years of experience in a data engineering, data pipeline, or ETL/ELT development role.
• Strong proficiency in SQL and data transformation logic for large datasets.
• Proficiency with Python and libraries such as Pandas, PySpark, or Numpy.
• Experience with modern version control and CI/CD practices (e.g., GitHub Actions, Jenkins).
• Understanding of distributed computing solutions for data processing (e.g. AWS Glue, AWS EMR, Apache Hadoop, Apache Spark).
• Experience with data pipeline orchestration frameworks or serverless tools (e.g., AWS StepFunctions, AWS Glue Workflows, and/or AWS Lambda).

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines using structured and semi-structured data from relational databases, flat files, APIs, and cloud data sources.
• Collaborate with backend and architecture teams to define data transformation flows aligned with dashboard and reporting application needs.
• Design and optimize data schemas to ensure performance, integrity, and compatibility with reporting requirements.
• Develop and maintain efficient, testable, and reusable data processing scripts using Python, SQL, and cloud-native tools.
• Collaborate with DevOps, analysts, and application developers to align pipelines with system architecture, storage strategy, and reporting needs.
• Implement data quality and validation checks and document data lineage and pipeline logic for audit and reuse.
• Troubleshoot performance issues in data jobs and support data pipeline operations across environments (DEV, VAL, PROD).
• Contribute CI/CD workflows and automation strategies to promote rapid iteration and secure deployment of data services.
• Assist in developing or maintaining data documentation, including metadata, data dictionaries, and technical user guides.
• Stay up to date with emerging technologies, techniques, and trends to inform product development and decision-making.

Skills

SQL

Python programming

CI/CD practices

Data transformation

Distributed computing concepts

Education

Bachelor's degree in computer science, engineering, statistics, or related field

Tools

GitHub Actions

Jenkins

AWS Glue

AWS EMR

Apache Hadoop

Apache Spark

AWS StepFunctions

AWS Lambda

Job description

Magpie Health Analytics, Inc. is seeking a Data Engineer to design, build, and optimize cloud-native data pipelines supporting healthcare clients. You will collaborate with backend and architecture teams to enable analytics, reporting, and decision-making.

Responsibilities include ETL/ELT development, data schemas, data quality checks, and documentation. The role emphasizes scalable, testable code, CI/CD workflows, and staying current with evolving data technologies.