Senior Cloud Data Engineer (Remote) — Databricks & PySpark

Geisinger; New York (NY); Remote; USD 120,000 - 180,000; Full time

Job summary

Geisinger is seeking a Senior Data Engineer to transform and manage clinical and genomic data in a Databricks/AWS environment. You will model data, build scalable pipelines, and modernize legacy ETL for cloud workloads.

You will collaborate with researchers and data stewards, ensure data quality and monitoring, and optimize Spark/SQL workloads across large datasets in a hybrid remote setup.

Qualifications

• Proven experience with Databricks and cloud-based data engineering platforms.
• Strong SQL and Python/PySpark for developing and optimizing data processing pipelines.
• Experience with Apache Spark or other distributed data processing technologies.
• Experience designing and implementing data models and data warehouse schemas for large-scale datasets.
• Experience developing, maintaining, or modernizing ETL processes and data pipelines.
• Experience working with relational databases and SQL Server.

Responsibilities

• Designs, develops, and maintains PySpark and SQL data pipelines for transforming clinical data for research use.
• Develops and maintains data models for clinical and other research data within the Databricks environment.
• Reviews, analyzes, modifies, creates, debugs, designs, and tests data ingestion and processing pipelines using modern development methodologies and tools.
• Defines and optimizes data warehouse schemas and data models to support efficient querying, storage, and analytical workflows.
• Ensures scalability, reliability, and maintainability of data pipelines and data architecture supporting large clinical and research datasets.
• Implements and monitors data quality checks and validation processes to ensure accuracy, completeness, and integrity of data throughout the pipeline.
• Troubleshoots and optimizes Spark and SQL workloads, data pipelines, and Databricks compute resources to improve performance and reliability.
• Modernizes existing on-premises Microsoft SQL Server ETL processes by designing and implementing equivalent cloud-based data pipelines and workflows in Databricks.
• Provides general Databricks computing support, including assisting users with compute resource selection, troubleshooting, and optimization of Spark and SQL workloads.
• Participates in design and application architecture discussions and assists in the development and documentation of technical approaches and solutions for team stakeholders.
• Responsible for the process, life cycle and creation of the software to assist users in completing a computer task or program.
• Implements code and documents all system changes based on assignments and timelines.
• Develops and follows department coding and user interface guidelines.
• Provides code review, testing, debugging, technical documentation, general testing instructions, go-live planning, assistance in go-live moves, and post-live support.
• Communicates all progress, roadblocks, and issues to the team and management in a timely manner.
• Collaborates with team members to identify and resolve issues, improve system performance, and ensure code quality.
• Provides training and documentation to team members on new development assignments.

Skills

Databricks

AWS

SQL

Python

PySpark

Spark

ETL

Data Modeling

Data Warehouse

Data Quality

Monitoring

Communication

Teamwork

Education

High School Diploma or GED

Bachelor's Degree in Technology

Tools

SQL Server

Databricks

AWS

Job description

Geisinger is seeking a Senior Data Engineer to transform and manage clinical and genomic data in a Databricks/AWS environment. You will model data, build scalable pipelines, and modernize legacy ETL for cloud workloads.

You will collaborate with researchers and data stewards, ensure data quality and monitoring, and optimize Spark/SQL workloads across large datasets in a hybrid remote setup.