{"id":3527200,"url":"https://alion.io/job/sunmed-data-engineer","title":"Data Engineer","company":{"id":3162899,"name":"SunMed","domain":"myairlife.com","url":"https://alion.io/company/myairlife","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"ADP","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Grand Rapids, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":75000,"max_usd":161000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":376},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"21 CFR Part 820","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"ISO 13485","optional":false},{"name":"LLM","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-30T14:39:19Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-10-31T18:39:23Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"COMPANY DESCRIPTION\nAt AirLife, we are dedicated to improving the quality of every breath. Excellence with Every Breath is not just a tag line, but the way we work and take care of our customers. With a mindset to evolve, innovate, and grow, we are a premier manufacturer of the highest-quality and market-leading breathing consumables. This growth philosophy has positioned us to increase our global footprint and business reach, impacting even more people around the world. Our expanding family of the most trusted brands offers a product portfolio that spans the continuum of care from first responder to home care, with safety, patient comfort, and clinical performance in mind. Collective expertise allows us to provide quality products and experiences to our patients, customers, and our people. Our values of Customer first, Differentiate with our People, Bias for Action, Continuous Improvement and Accountability define who we are and how we work. Join us!\nPOSITION SUMMARY\nThe Data Engineer is the hands-on builder and operator of AirLife’s Databricks Lakehouse, reporting to the Data Engineering & Platform Manager. This role builds, operates, and improves the pipelines that bring data from SAP ECC, Microsoft Dynamics GP, Salesforce, and other operational systems into the Lakehouse, and applies the governance, architecture, and cost standards the Manager defines. As AirLife’s analytics and AI platform matures, this role is the execution layer that keeps pipelines reliable, documented, and ready for business and AI consumption.\nPOSITION QUALIFICATIONS\nKnowledge, Skills, & Abilities:\nHands-on, production experience building on Databricks: Delta Lake, Unity Catalog, Databricks Workflows / Lakeflow Jobs, and Lakeflow Declarative Pipelines. \nStrong Python and PySpark for data engineering; advanced SQL. \nExperience ingesting ERP and CRM data into a lakehouse; SAP ECC required or strongly preferred, Microsoft Dynamics GP and Salesforce a plus. \nWorking knowledge of Azure data services: Azure Data Lake Storage Gen2, Azure Data Factory, Azure SQL, and Azure Key Vault. \nSoftware engineering practices applied to data: Git, pull requests and code review, CI/CD (Databricks Asset Bundles, Azure DevOps, or GitHub Actions), and automated data quality tests. \nPractical understanding of Unity Catalog access controls, row- and column-level security, and data classification. \nExperience implementing medallion architecture (bronze/silver/gold) and dimensional modeling for analytics consumption. \nWorking knowledge of data cataloging, lineage, and metadata management practices. \nAwareness of data privacy and classification expectations in an FDA-regulated / ISO 13485 manufacturing environment. \nAbility to read someone else's pipeline, figure out what it does and why, and take ownership of it. \nPreferred:\nBuilding data products for AI consumption: Databricks Genie / AI/BI, Databricks Apps, vector search, or serving curated data to LLM-based tools. \nExperience with cost-aware engineering on Databricks - cluster and job right-sizing, serverless trade-offs, and reading system tables for usage. \nExperience taking over work from consultants or offshore partners, running it in-house, and mentoring less-experienced engineers through the transition. \nExposure to Power BI as a downstream consumer of lakehouse data. \nInfrastructure-as-code (Terraform) for Databricks/Azure resources. \ndbt (data build tool) or equivalent transformation framework experience.\nLevel of Experience:\n2+ years of hands-on Databricks pipeline development in an enterprise environment. Manufacturing, healthcare, or life sciences data experience preferred.\nLevel of Education:\nBachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience. Databricks Certified Data Engineer Associate or Professional preferred. \nTravel:\nUp to 10% as required by the business.\nESSENTIAL DUTIES AND RESPONSIBILITIES\nBuild, test, and deploy data pipelines - including medallion (bronze/silver/gold) layers - that ingest data from SAP ECC, Microsoft Dynamics GP, Salesforce, and other operational systems into the Databricks Lakehouse, using batch and incremental patterns and the architecture standards set by the Data Engineering & Platform Manager. \nTake ownership of pipelines, notebooks, and data models built by external implementation partners: lead the technical side of knowledge transfer, document what exists, close gaps, and run it in production. \nOperate what you build: monitor job health and data freshness, triage failures, fix root causes, and keep downstream teams informed when data is late or wrong. \nWrite data quality checks into pipelines (expectations, reconciliations to source, row-count and null-rate monitors) and act on what they find. \nApply Unity Catalog governance standards in daily work - naming, tagging, ownership, lineage documentation, metadata management, and access grants - as defined by the Data Engineering & Platform Manager. \nImplement data security and access controls on the data you manage, consistent with AirLife's data classification standards and FDA 21 CFR Part 820 / ISO 13485 data-integrity expectations. \nParticipate in integration design reviews and new data source onboarding evaluations led by the Data Engineering & Platform Manager, and partner with Commercial Analytics, Supply Chain Analytics, Master Data, and the AI Lead to translate their requirements into pipeline and data model changes that support self-service BI and AI use cases. \nSupport integrations that write data back to operational systems; keep code in source control, work through pull requests, and deploy through CI/CD. \nWrite and maintain runbooks and technical documentation, including data lineage and pipeline architecture documentation. \nWatch compute cost and performance on the jobs you own - right-size clusters and schedules, tune queries and pipelines (partitioning, caching), flag risks early, and provide usage data from Databricks system tables to support the Manager's cost governance. \nBring forward improvements to standards, patterns, and tooling. \nSupport the onboarding and technical mentoring of junior data engineers or offshore/outsourced engineering resources as the team grows.\nOTHER RESPONSIBILITIES\nUphold and embody AirLife’s values in all aspects of work.\nDemonstrate accuracy and thoroughness in daily work; look for ways to improve and promote quality & safety. \nInspire the trust of others; treat people with respect and dignity and embrace the value of diversity.\nUse time efficiently; perform job accurately, thoroughly, and conserve Company resources to improve profits.\nContribute to building and maintaining a positive team environment.\nAssure all policies and guidelines are implemented and followed.\nQUALITY POLICY\nAt AirLife, Quality is our promise. It is our commitment to customer satisfaction and our dedication to product excellence in an evolving global healthcare market. This promise is kept through a continuously improving and effective Quality Management System and compliance to Regulatory Requirements.\nDEIA STATEMENT\nAt AirLife, we are committed to building a diverse workforce and an inclusive workplace that reflects the communities and customers we serve. We believe our philosophy on Diversity, Equity, Inclusion, and Advancement (DEIA) encourages excellence and equips us to serve an evolving global marketplace.\nBENEFITS\nAirLife offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k), paid time off, paid holidays, bereavement leave, Employee Assistance Program resources, and medical leave benefits, subject to applicable eligibility requirements. Certain positions may also be eligible for bonus, commission, or other incentive compensation.\nPlease note: The responsibilities outlined above are not exhaustive and may evolve over time. 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