Python Data Engineer

Job Description

Job Description

Salary :

Start Date : 05 / 26 / 2025

Job Description

Title : Python Data Engineer

Location : Remote

Type : Temp to Perm

Description :

We are looking for a Python Data Engineer that will bring strong expertise in CMS datasets

(MOR, MMR, MAO) and an understanding of healthcare regulations. The role requires

proficiency with modern cloud data engineering tools, including Dataflow, BigQuery, and

Airflow for orchestration, along with solid foundational knowledge in data warehousing

concepts and optimization techniques for large healthcare datasets.

What You Will Do :

Design, develop, and maintain scalable ETL pipelines for CMS datasets using GCP

Dataflow and Python.

Architect and manage data warehouses using BigQuery, ensuring scalability and

cost-efficiency.

Implement Airflow DAGs for orchestration of complex data workflows and

scheduling.

Ensure data quality, validation, lineage, and governance aligned with CMS and

HIPAA compliance standards.

Optimize large-scale datasets through partitioning, clustering, sharding, and cost

effective query patterns in BigQuery.

Work collaboratively in Agile teams, using Jira for project tracking and Confluence

for documentation.

Monitor and troubleshoot data pipelines, ensuring reliability and operational

excellence.

You Will Be Successful If :

Self-motivated, proactive, and capable of thriving in a fast-paced, agile startup

environment with minimal supervision.

Demonstrates strong ownership of tasks and deliverables, acting as a task master.

Eager self-learner who stays current with emerging technologies and industry

trends.

Excellent communication skills, both written and verbal, to effectively collaborate

across multidisciplinary teams.

What You Will Bring :

Bachelor's degree in Computer Science, Information Systems, or related field.

7+ years of experience in cloud-based data engineering, preferably with healthcare

datasets.

Extensive experience working with risk adjustment.

Expertise in building ETL pipelines using GCP Dataflow (Apache Beam) and Python.

Expert experience with BigQuery including schema design, optimization, and

advanced SQL.

Hands-on experience with Airflow orchestration for large-scale data workflows.

Deep understanding of data warehouse concepts such as star schema, snowflake

schema, normalization, denormalization.

Expert in dataset optimization techniques : query optimization, partitioning,

clustering.

Familiarity with Agile processes, Jira, Confluence, and cloud-native engineering best

practices.

Knowledge of CMS datasets (MOR, MMR, MAO) and healthcare data compliance

(HIPAA).