Data Engineer — dbt, Cloud Lakehouse & SQL

Insight Global; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Insight Global is seeking a data/analytics engineer to design and productionize dbt projects, build scalable SQL data pipelines, and collaborate with clinical operations and governance teams.

The ideal candidate will own dbt projects, implement CI/CD, work with Databricks or Snowflake, Python, and orchestration tools, and communicate modeling decisions clearly in a fast-paced healthcare data environment.

Qualifications

• 3-6 years in data/analytics engineering with 2+ years owning dbt projects in production.
• Strong SQL with window functions, joins, and performance tuning on large datasets.
• Expert dbt knowledge: materializations, snapshots, tests, macros, packaging, project structure.
• Hands-on Git and PR-based CI/CD; promote data changes across environments.
• Experience with a CI platform (CircleCI, GitHub Actions, GitLab CI, or Azure DevOps).
• Databricks Lakehouse or Snowflake/BigQuery experience; Python for ingestion and tooling.
• Workflow orchestration experience: Prefect, Airflow, Dagster, or Databricks Workflows.
• Dimensional modeling knowledge; data governance and HIPAA PHI handling.
• Clear written communication; explain modeling decisions to engineers and ops.
• Able to thrive in a fast-paced, evolving environment.
• Healthcare data experience: claims, EHR, HEDIS, RAF/HCC, value-based care.

Skills

dbt production

SQL expertise

Python data tooling

Git and CI/CD

Cloud lakehouse

Workflow orchestration

Dimensional modeling

HIPAA data handling

Communication skills

Fast-paced environment

Tools

Postgres

Snowflake

BigQuery

Databricks

Airflow

Dagster

Prefect

Terraform

Docker

GitHub Actions

CircleCI

Job description

Insight Global is seeking a data/analytics engineer to design and productionize dbt projects, build scalable SQL data pipelines, and collaborate with clinical operations and governance teams.

The ideal candidate will own dbt projects, implement CI/CD, work with Databricks or Snowflake, Python, and orchestration tools, and communicate modeling decisions clearly in a fast-paced healthcare data environment.