Data Integration Engineer II

mPulse; United States; On-site; USD 110,000 - 150,000; Full time

Job summary

mPulse is seeking a data operations professional to design, develop, and maintain scalable data pipelines powering analytics and product capabilities. You will collaborate with product engineering, implementation, analytics, and customer success to ensure accurate, reliable data across multiple sources.

The ideal candidate has strong SQL, data warehousing experience, and a passion for building well-documented data systems while working with AWS, Snowflake, Airflow, and dbt in a fast-paced

Qualifications

• Bachelor’s or Master’s degree in computer science, engineering, or related field; or equivalent practical experience.
• Minimum of 3 years in data engineering, data integration, or related role.
• Strong SQL proficiency including complex querying and optimization.
• Experience with cloud data platforms on AWS and modern data warehouses (Snowflake, Redshift, etc.).
• Experience with Airflow DAGs and orchestration; dbt for modular transformations.
• Version control with GitHub or similar; Python for data tasks.
• Experience with CI/CD tools (Jenkins, GitHub Actions).
• Excellent communication across technical and non-technical teams.

Responsibilities

• Design, develop, and maintain scalable data pipelines (ETL/ELT) for ingestion, transformation, cleansing, and unification across data sources.
• Build end-to-end pipeline components: ingestion, validation, transformation, and curated data layers.
• Monitor and optimize production pipelines for reliability and performance.
• Create technical documentation for data pipelines, workflows, and data models.
• Develop data profiling, quality monitoring, and unit testing frameworks.
• Collaborate with implementation teams to resolve data onboarding issues.
• Partner with product engineering to align data capture with app specs and business needs.
• Provide data support to analytics and customer success teams for reporting and inquiries.

Skills

SQL proficiency

Python scripting

Data modeling

Cross-team collaboration

Education

Bachelor’s or Master’s in CS/Engineering or related field

Tools

AWS (S3, Secrets Manager/Vault, DMS)

Snowflake

PostgreSQL

Redshift

MS SQL Server

Airflow

dbt

GitHub

Jenkins

Job description

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 [e-mail]