Data Integration Engineer I — Remote & Growth Opportunities

re-zoo-me; Los Angeles (CA); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Remote-friendly environment

Comprehensive healthcare coverage

401(k) with 4% match

6 weeks parental leave

Job summary

mPulse is seeking a curious Data Engineer to join the Data Operations team. Build, operate, and improve healthcare data pipelines powering analytics and AI platforms. You will collaborate with engineers, analysts, and implementation teams to ensure data is ingested, processed, and delivered accurately.

Ideal for those early in their data engineering career who enjoy complex real-world data and growth in modern data platforms within a healthcare tech environment.

Qualifications

• Bachelor's degree or equivalent practical experience in a technical field.
• Proficiency in SQL and relational databases; ability to write analysis/transform queries.
• Experience with Python or similar scripting for data processing.
• Familiarity with ETL/ELT concepts and data pipeline fundamentals.
• Strong analytical/problem-solving skills and ability to explain technical concepts clearly.
• Excellent written and verbal communication with stakeholders.

Responsibilities

• Monitor and support daily operation of production data pipelines.
• Troubleshoot pipeline failures and resolve data processing issues.
• Investigate data quality issues within healthcare datasets.
• Perform data validation for accuracy, completeness, and consistency.
• Analyze datasets to identify patterns and data issues.
• Collaborate with implementation teams on client data formats and integration.

Skills

SQL

Python

ETL/ELT

Data pipelines

Analytics

Communication

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Snowflake

Apache Airflow

Jenkins

PowerShell

Job description

mPulse is seeking a curious Data Engineer to join the Data Operations team. Build, operate, and improve healthcare data pipelines powering analytics and AI platforms. You will collaborate with engineers, analysts, and implementation teams to ensure data is ingested, processed, and delivered accurately.

Ideal for those early in their data engineering career who enjoy complex real-world data and growth in modern data platforms within a healthcare tech environment.