Remote Data Engineer - Self-Service Data Platform

Hispanic Alliance for Career Enhancement; Washington (District of Columbia); Hybrid; USD 64,890 - 173,040; Full time

Job summary

CVS Health is hiring a fully remote Data Engineer to join the Data Engineering team. You will design, develop, and maintain data pipelines and platform infrastructure powering a self-service application, collaborating with senior engineers for guidance and code reviews.

You will work with modern data platforms, gain autonomy on defined tasks, and contribute to observability, testing, and deployment across the SDLC.

Qualifications

• 2 years of professional data engineering or software development experience.
• Strong proficiency in SQL - writing, optimizing, and troubleshooting complex queries.
• Experience with at least one cloud data warehouse or data platform (Snowflake, BigQuery, Redshift, Azure Synapse, or Databricks).
• Proficiency with Git-based version control, including branching, pull requests, and code review workflows.
• Familiarity with CI/CD concepts and automated deployment workflows (GitHub Actions).

Responsibilities

• Build, maintain, and improve data pipelines and ETL/ELT processes using Python.
• Write and optimize SQL queries to support data ingestion, transformation, troubleshooting, and validation.
• Contribute to data modeling efforts and maintain data integrity within Snowflake.
• Integrate with Kafka-driven event streams for real-time ingestion.
• Write clean, well-tested code and ensure unit/integration test coverage.

Skills

SQL

Python

Git workflows

CI/CD

Education

Bachelor's degree in CS, Data Eng, IS, or related

Tools

Snowflake

BigQuery

Amazon Redshift

Azure Synapse Analytics

Databricks

Job description

CVS Health is hiring a fully remote Data Engineer to join the Data Engineering team. You will design, develop, and maintain data pipelines and platform infrastructure powering a self-service application, collaborating with senior engineers for guidance and code reviews.

You will work with modern data platforms, gain autonomy on defined tasks, and contribute to observability, testing, and deployment across the SDLC.