Remote Data Engineer

A client in the insurance/annuities space is looking for a highly skilled Data Engineer to join their enterprise data engineering and delivery team. These resource will contribute to modernizing the data ecosystem and enabling high-quality, business-ready data across the organization. This role focuses on building scalable data pipelines, transforming raw data into usable assets, and ensuring data reliability for their insurance and annuity operations. Success in this role requires strong Python and SQL skills, deep curiosity about the why behind the data, and the ability to translate engineering work into meaningful business impact. You will work self-directed on complex problems, contribute to the migration from legacy systems to a modern tech stack, and help the business make better decisions through trustworthy, well-engineered data. This is an opportunity to influence how data is delivered, understood, and used to drive behavior and outcomes across the organization. The ideal candidate will be looking for $65-75/hr.

Core responsibilities include:

Building and maintaining scalable data pipelines using Python, SQL, and Git

Developing high-quality transformations using Coalesce or DBT

Supporting the migration from legacy systems (SSIS, stored procedures, Azure DevOps) into the new Snowflake-based stack

Implementing orchestration workflows using Dagster

Ensuring data quality using Datafold

Troubleshooting data issues by digging into root causes and understanding business impact

Collaborating with analysts and business teams to understand what the data means and how it drives decisions

5+ years of experience as a Data Engineer building and supporting production data pipelines

-Strong proficiency in Python, SQL, and Git within modern data environments

-Experience with cloud data platforms and processing frameworks (Snowflake, Databricks, Spark)

-Hands-on experience with analytics engineering tools such as dbt or Coalesce

-Experience using DAG-based orchestration tools (Airflow, Dagster) and data quality frameworks

-Strong problem-solving, communication skills, and curiosity about how data impacts business outcomes, with exposure to finance/insurance/annuity data -Understanding of infrastructure and cloud networking concepts (e.g., AWS private endpoints)

-Experience migrating from legacy systems (SSIS, stored procedures, Azure DevOps)

-Ability to influence technical decisions or improve engineering practices

-Prior mentorship experience with junior engineers