Senior Data Engineering Developer

Geisinger Clinic; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Remote work

Job summary

Geisinger Clinic’s Research Data Core seeks a Senior Data Engineer to design and maintain cloud-based data platforms and scalable pipelines. You will model clinical data in Databricks, build ETL processes, and modernize legacy pipelines for a research-focused environment.

The role emphasizes data quality, performance optimization, monitoring, and collaboration with multidisciplinary teams to support analytics and research applications.

Qualifications

• Proven experience with Databricks and cloud-based data engineering platforms.
• Strong experience with SQL and Python/PySpark for developing and optimizing data processing pipelines.
• Experience with Apache Spark and data modeling for large-scale datasets.

Responsibilities

• Designs and maintains PySpark and SQL data pipelines for transforming clinical data for research use.
• Develops and maintains data models and data warehouse schemas for large-scale datasets.
• Reviews, tests, debugs, and optimizes data ingestion and processing pipelines.
• Implements data quality checks and monitors pipeline performance and reliability.
• Collaborates with team to design solutions and document technical approaches.

Skills

Databricks

Python/PySpark

SQL

Cloud computing

Spark

Data pipelines

Education

Bachelor's degree in a related field

Tools

Databricks

AWS

SQL Server

PySpark

Job description

Location: Work from home (Pennsylvania)

Shift: Days (United States of America)

Scheduled Weekly Hours: 40

Worker Type: Regular

Exemption Status: Yes

Job Summary

The Geisinger Research Data Core is responsible for transforming and managing clinical and genomic data for research use. As part of a collaborative and multidisciplinary team, this position develops and maintains data systems and pipelines that support research applications and the use of large-scale clinical and genomic datasets. The role provides key insight into data architecture, data modeling, and application development and engages in all aspects of the development life cycle as needed for each project to be successful.

We are seeking a skilled Senior Data Engineer with experience in cloud-based data platforms, particularly the Databricks platform and AWS. The ideal candidate will be responsible for modeling clinical data within the Databricks environment, developing and maintaining scalable data pipelines, and modernizing legacy ETL processes for cloud environments. The position will also support data quality, performance optimization, monitoring, and general Databricks computing needs for research and analytical applications.

Job Duties

• 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.
• Trains and mentors staff members.
• Assists in the development and documentation of a technical approach for a solution to the team stakeholders.

Work is typically performed in an office environment. Accountable for satisfying all job specific obligations and complying with all organization policies and procedures. The specific statements in this profile are not intended to be all-inclusive. They represent typical elements considered necessary to successfully perform the job.

Relevant Experience

*Relevant experience may be a combination of related work experience and degree obtained (Associate's Degree = 2 years; Bachelor's Degree = 4 years; Master's Degree = 6 years).

Position Details

Requirements

• Proven experience with Databricks and cloud-based data engineering platforms.
• Strong experience with 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
• Experience migrating or modernizing on-premises ETL processes is preferred.
• Familiarity with AWS cloud services and cloud-based data architectures.
• Experience with data quality, validation, monitoring, logging, and troubleshooting practices.
• Understanding of data pipeline performance optimization and scalable data processing.
• Excellent communication skills to convey progress, roa