Data Integration Engineer II

Sorry, this job was removed at 08:20 p.m. (UTC) on Wednesday, Oct 14, 2026
Hiring Remotely in United States
Remote
Mid level
Artificial Intelligence • Healthtech • Software • Analytics
The Role
Design, develop, and maintain scalable ETL/ELT data integration pipelines supporting analytics, reporting, and product capabilities. Build ingestion, transformation, validation, and curated data layers; optimize production workflows; document systems; and implement data quality monitoring and testing. Collaborate with implementation, engineering, analytics, and customer success teams to resolve data issues, support onboarding, and ensure reliable, accessible data.
Summary Generated by Built In

About mPulse:  mPulse is the leader in conversational AI and member engagement for healthcare. We partner with the nation's most innovative health plans — Medicare Advantage, Medicaid, and Commercial — to engage members in conversations that close care gaps, improve Stars ratings, and drive better health outcomes. Our platform reaches tens of millions of Americans and is built on the belief that better health starts with better conversations.

Job Summary

We’re looking for a passionate, self-motivated, and detail-oriented individual to join our Data Operations team. In this role, you will design, develop, and maintain scalable data pipelines that power analytics, reporting, and product capabilities within the predict vertical of the organization.

 

You will work closely with product engineering, implementation, analytics, and customer success teams to ensure data is accurate, reliable, and accessible. The ideal candidate has strong SQL and data warehousing experience, enjoys solving complex data problems, and is passionate about building reliable and well-documented data systems.

 

Duties & Responsibilities

  • Design, develop, and maintain scalable data integration pipelines (ETL/ELT) to support data ingestion, transformation, cleansing, curation, and unification across multiple data sources.
  • Develop and support end-to-end data pipeline components, including ingestion, validation, transformation, cleansing, and curated data layer development.
  • Monitor, maintain, and optimize production data pipelines to ensure reliability, performance, and successful execution of scheduled workflows.
  • Create and maintain comprehensive technical documentation for data pipelines, workflows, and data models.
  • Develop tools and frameworks to support automated data profiling, data quality monitoring, and unit testing to ensure high-quality and reliable data assets.
  • Collaborate with implementation teams to identify, investigate, and resolve data anomalies during data onboarding and integration processes.
  • Partner with product engineering teams to ensure accurate data capture and alignment with application data specifications and business requirements.
  • Provide data-related support to analytics and customer success teams, assisting with troubleshooting, reporting needs, and client data inquiries.

 

Required Qualifications

  • Bachelor’s or master’s degree in computer science, Engineering, or a related technical field, or equivalent practical experience.
  • Minimum of 3 years of professional experience in data engineering, data integration, or a related role.
  • Strong proficiency in SQL, including complex querying, data transformation, and query performance optimization.
  • Experience working with cloud-based data platforms and services, particularly within AWS (e.g., S3, Secrets Manager/Vault, DMS, or similar services).
  • Hands-on experience with modern data warehousing platforms, such as Snowflake, PostgreSQL, Amazon Redshift, or Microsoft SQL Server.
  • Experience developing, debugging, and maintaining workflow orchestration pipelines using Apache Airflow, including DAG development and operational support.
  • Experience using dbt (data build tool) to develop, test, and manage modular SQL-based data transformation models within modern data warehouse environments.
  • Experience with version control systems and collaborative development workflows, using tools such as GitHub or Bitbucket.
  • Proficiency in Python, particularly for data manipulation, automation, and integration tasks.
  • Familiarity with CI/CD practices and automation tools, such as Jenkins or GitHub Actions.
  • Strong written and verbal communication skills, with the ability to collaborate effectively across technical and non-technical teams.

 

Preferred Qualifications

  • Experience supporting data quality monitoring, data observability, or automated validation frameworks.
  • Familiarity with data science or machine learning workflows from a data engineering perspective.
  • Experience working with healthcare-related datasets, such as claims, clinical, or regulatory data.

 

 

*Please note, due to the requirements of this position, responses may automatically disqualify you from moving forward in the application process. Please review minimum qualifications thoroughly before applying.  

 

Why Join our team?

You will have the opportunity to work on modern data platforms and tools, collaborate with cross-functional teams, and help build reliable data systems that drive meaningful insights and business value.

 

We’re as passionate about our people as we are about making our mark on healthcare. Fostering a fun and challenging environment that’s centered around personal and professional growth has brought us to where we are today. We are constantly seeking out new ways to reinvest in our team members because let’s face it, we all do our best work when we feel valued.

If you require any accommodations during the application, interview, or assessment process due to a disability or any other accessibility-related concern, please do not hesitate to reach out to our People Ops and Recruiting team at [email protected]

Skills Required

  • Bachelor’s or master’s degree in computer science, engineering, or a related technical field, or equivalent practical experience
  • At least 3 years of professional experience in data engineering, data integration, or a related role
  • Strong proficiency in SQL, including complex querying, data transformation, and query performance optimization
  • Experience with cloud-based data platforms and services, particularly AWS
  • Hands-on experience with modern data warehousing platforms such as Snowflake, PostgreSQL, Amazon Redshift, or Microsoft SQL Server
  • Experience developing, debugging, and maintaining Apache Airflow workflow orchestration pipelines, including DAG development and operational support
  • Experience using dbt to develop, test, and manage modular SQL-based data transformation models
  • Experience with version control systems and collaborative development workflows using GitHub or Bitbucket
  • Proficiency in Python for data manipulation, automation, and integration tasks
  • Familiarity with CI/CD practices and automation tools such as Jenkins or GitHub Actions
  • Strong written and verbal communication skills with the ability to collaborate across technical and non-technical teams
  • Experience supporting data quality monitoring, data observability, or automated validation frameworks
  • Familiarity with data science or machine learning workflows from a data engineering perspective
  • Experience working with healthcare-related datasets, such as claims, clinical, or regulatory data

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The Company
HQ: Los Angeles, CA
631 Employees
Year Founded: 2015

What We Do

mPulse is a health experience and insights technology company serving healthcare organizations. It combines predictive analytics, AI-driven digital engagement, omnichannel outreach, health navigation, portals, content management, and acquisition/payment tools to improve consumer health outcomes and business efficiency at scale. Following its acquisition of Clarity Software Solutions, the company also supports regulated health-plan communications through an integrated print, mailing, and software-services capability.

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