{"id":3228361,"url":"https://alion.io/job/geisinger-senior-data-engineering-developer","title":"Senior Data Engineering Developer","company":{"id":1774033,"name":"Geisinger","domain":"geisinger.org","url":"https://alion.io/company/geisinger","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":76,"open_postings":138,"ghost_share":0,"stale_share":0.942,"repost_share":0,"time_to_fill_p50_days":34,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":93000,"max_usd":175000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1343},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"MS SQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-22T00:00:00Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-11-12T17:13:11Z","board_verified":true,"closed_at":null,"days_open":21,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":21},"description":"Location:\nWork from home (Pennsylvania)Shift:\nDays (United States of America)Scheduled Weekly Hours:\n40Worker Type:\nRegularExemption Status:\nYesJob Summary:\nThe 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.\nJob Duties:\nDesigns, develops, and maintains PySpark and SQL data pipelines for transforming clinical data for research use.\nDevelops and maintains data models for clinical and other research data within the Databricks environment.\nReviews, analyzes, modifies, creates, debugs, designs, and tests data ingestion and processing pipelines using modern development methodologies and tools.\nDefines and optimizes data warehouse schemas and data models to support efficient querying, storage, and analytical workflows.\nEnsures scalability, reliability, and maintainability of data pipelines and data architecture supporting large clinical and research datasets.\nImplements and monitors data quality checks and validation processes to ensure accuracy, completeness, and integrity of data throughout the pipeline.\nTroubleshoots and optimizes Spark and SQL workloads, data pipelines, and Databricks compute resources to improve performance and reliability.\nModernizes existing on-premises Microsoft SQL Server ETL processes by designing and implementing equivalent cloud-based data pipelines and workflows in Databricks.\nProvides general Databricks computing support, including assisting users with compute resource selection, troubleshooting, and optimization of Spark and SQL workloads.\nParticipates in design and application architecture discussions and assists in the development and documentation of technical approaches and solutions for team stakeholders.\nResponsible for the process, life cycle and creation of the software to assist users in completing a computer task or program.\nImplements code and documents all system changes based on assignments and timelines.\nDevelops and follows department coding and user interface guidelines.\nProvides code review, testing, debugging, technical documentation, general testing instructions, go-live planning, assistance in go-live moves, and post-live support.\nCommunicates all progress, roadblocks, and issues to the team and management in a timely manner.\nCollaborates with team members to identify and resolve issues, improve system performance, and ensure code quality.\nProvides training and documentation to team members on new development assignments.\nTrains and mentors staff members.\nAssists in the development and documentation of a technical approach for a solution to the team stakeholders.\nWork 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.\n*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).\nPosition Details:\nRequirements:\nProven experience with Databricks and cloud-based data engineering platforms.\nStrong experience with SQL and Python/PySpark for developing and optimizing data processing pipelines.\nExperience with Apache Spark or other distributed data processing technologies.\nExperience designing and implementing data models and data warehouse schemas for large-scale datasets.\nExperience developing, maintaining, or modernizing ETL processes and data pipelines.\nExperience working with relational databases and SQL Server\nExperience migrating or modernizing on-premises ETL processes is preferred.\nFamiliarity with AWS cloud services and cloud-based data architectures.\nExperience with data quality, validation, monitoring, logging, and troubleshooting practices.\nUnderstanding of data pipeline performance optimization and scalable data processing.\nExcellent communication skills to convey progress, roadblocks, technical issues, and solutions to team members and management.\nAbility to work effectively as part of a multidisciplinary team and collaborate with technical and research stakeholders.\nEducation:\nHigh School Diploma or Equivalent (GED)- (Required), Bachelor's Degree-Technology Related Degree (Preferred)Experience:\nMinimum of 10 years-Related work experience (Required)Certification(s) and License(s):\nSkills:\nCritical Thinking, Interpersonal Communication, Leads OthersOUR PURPOSE & VALUES: Everything we do is about caring for our patients, our members, our students, our Geisinger family and our communities.\nKINDNESS: We strive to treat everyone as we would hope to be treated ourselves. \nEXCELLENCE: We treasure colleagues who humbly strive for excellence. \nLEARNING: We share our knowledge with the best and brightest to better prepare the caregivers for tomorrow. \nINNOVATION: We constantly seek new and better ways to care for our patients, our members, our community, and the nation.\n SAFETY: We provide a safe environment for our patients and members and the Geisinger family. \nWe offer healthcare benefits for full time and part time positions from day one, including vision, dental and domestic partners. Perhaps just as important, we encourage an atmosphere of collaboration, cooperation and collegiality.\nEqual Opportunity Employer. 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