Data Integration Engineer I

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee and provide support for the daily functioning of production data pipelines.

• Diagnose pipeline failures and assist in resolving data processing challenges, escalating complex issues when necessary.

• Investigate and help address data quality challenges, anomalies, and discrepancies within healthcare datasets.

• Conduct data validation and testing to ensure the accuracy, completeness, and consistency of integrated data.

• Analyze datasets to identify patterns, irregularities, and potential data issues.

• Collaborate with implementation teams to comprehend client data formats and integration needs.

• Aid in data reconciliation and validation during client onboarding and integration processes.

• Write and enhance SQL queries for data transformations, validation, and analysis.

• Assist in the development, testing, and maintenance of data integration pipelines.

• Create and uphold documentation for data workflows, pipeline behavior, and operational procedures.

• Participate in code reviews and incorporate feedback to enhance code quality and development practices.

• Work across both current and target data platform environments and contribute to the migration process.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.

• Proficient in SQL with experience in relational databases, including writing queries for data analysis and transformation.

• Experience with scripting or automation using Python or a similar programming language to support data processing or integration tasks.

• Familiar with ETL/ELT concepts and data pipeline fundamentals, including data ingestion, transformation, and validation processes.

• Strong analytical and problem-solving abilities, with the capacity to investigate data issues and determine root causes.

• Excellent written and verbal communication skills, capable of clearly explaining technical concepts to both technical and non-technical stakeholders.

• Experience with healthcare data, including Medicare, Medicaid, or medical claims datasets.

• Familiarity with common healthcare code sets, such as ICD, CPT, or HCPCS.

• Exposure to modern data platforms and tools, such as Snowflake, Apache Airflow, or cloud-based data environments.

• Familiarity with CI/CD practices or tools, such as Jenkins or GitHub Actions.

• Understanding of data warehousing concepts, including dimensional modeling and analytics-oriented data structures.

🏝️ Benefits

• Remote-friendly environment.

• Opportunities for professional growth and skill development.

• Comprehensive healthcare coverage.

• Meaningful work with direct impact on healthcare outcomes.