Data Engineer: Scalable Pipelines for Analytics Platform

3GIMBALS; Virginia (MN); On-site; USD 110,000 - 160,000; Full time

Job summary

3GIMBALS is hiring a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure for an analytic platform. You will ingest, transform, and curate large volumes of data from diverse sources, ensuring high quality and governance for downstream analytics, knowledge graphs, and modeling teams.

The role requires comfort with multi-source data at scale in secure environments. The ideal candidate has 4+ years in data engineering, strong Python/SQL skills, and hands-on

Qualifications

• . 4+ years of data engineering experience building and operating production data pipelines.
• . Proficient in Python and SQL; experience with distributed processing (Spark, Dask, or similar).
• . Hands-on with workflow orchestration tools (Airflow, Dagster, Prefect).
• . Proficiency with relational and NoSQL databases; cloud data platforms (AWS, Azure, or GCP).
• . Experience designing data models, warehouses, and lakehouses; data quality and governance.

Responsibilities

• Design and build scalable batch and streaming data pipelines for structured and unstructured data.
• Model and store data across relational, NoSQL, and object stores; maintain data lakes/lakehouses.
• Ensure data quality, lineage, governance, and metadata management across pipelines.
• Support security and compliant data handling in sensitive environments.

Skills

Python

SQL

Spark

Airflow

Dagster

Prefect

Docker

Kubernetes

PostgreSQL

MongoDB

Tools

PostgreSQL

MongoDB

Elasticsearch

Airflow

Dagster

Prefect

Job description

3GIMBALS is hiring a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure for an analytic platform. You will ingest, transform, and curate large volumes of data from diverse sources, ensuring high quality and governance for downstream analytics, knowledge graphs, and modeling teams.

The role requires comfort with multi-source data at scale in secure environments. The ideal candidate has 4+ years in data engineering, strong Python/SQL skills, and hands-on