Data Integration Engineer I

mPulse is a healthcare technology company specializing in conversational AI and member engagement. The Data Integration Engineer I will support, troubleshoot, validate, and improve healthcare data pipelines while collaborating with engineering, analytics, and implementation teams to ensure accurate data integration for analytics and AI platforms.

Responsibilities:

• Monitor and support the daily operation of production data pipelines to ensure successful data processing and workflow execution
• Troubleshoot pipeline failures and assist in resolving data processing issues, escalating complex problems when necessary
• Investigate and help resolve data quality issues, anomalies, and discrepancies, particularly within healthcare datasets
• Perform data validation and testing to ensure accuracy, completeness, and consistency of integrated data
• Analyze datasets to identify patterns, irregularities, and potential data issues, supporting proactive data quality improvements
• Collaborate with implementation teams to understand client data formats and integration requirements
• Assist with data reconciliation and validation during client onboarding and integration processes
• Write and optimize SQL queries to support data transformations, validation, and analysis tasks
• Assist in the development, testing, and maintenance of data integration pipelines
• Create and maintain documentation for data workflows, pipeline behavior, and operational procedures
• Participate in code reviews and incorporate feedback to improve code quality and development practices

Requirements:

• • Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience
• • Proficiency in SQL and experience working with relational databases, including writing queries for data analysis and transformation
• • Experience with scripting or automation using Python or a comparable programming language to support data processing or integration tasks
• • Familiarity with ETL/ELT concepts and data pipeline fundamentals, including data ingestion, transformation, and validation processes
• • Strong analytical and problem-solving skills, with the ability to investigate data issues and identify root causes
• • Strong written and verbal communication skills, with the ability to clearly explain technical concepts to both technical and non-technical stakeholders
• • Experience working 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