Data Engineering & Platform Manager

AirLife•Grand Rapids, MI

15h

About The Position

The Data Engineering & Platform Manager is AirLife's technical owner of the enterprise data platform — responsible for building, governing, and continuously improving the data infrastructure that powers AirLife's analytics and AI capabilities. This role owns the Databricks environment and all associated data pipelines, ensuring that data flowing into the platform is accurate, well-governed, and accessible to the business intelligence and AI consumers who depend on it. As AirLife's analytics and AI ambitions grow, this role serves as the foundational layer — designing the data architecture, enforcing data quality and governance standards, and enabling the organization to trust and act on its data with confidence.

Requirements

Deep hands-on expertise with Databricks, including Unity Catalog, Delta Lake, Databricks Workflows, and the Lakehouse architecture pattern.
Experience leading a team and managing, mentoring, and evaluating team members
Experience designing and implementing end-to-end data pipelines using Azure Data Factory, Databricks Workflows, or equivalent orchestration tooling.
Strong proficiency with Microsoft Azure data services, including Azure Data Lake Storage Gen2, Azure Synapse Analytics, and Azure SQL.
Demonstrated experience implementing data governance frameworks, including data cataloging, data lineage, metadata management, and data quality rule enforcement.
Proficiency in SQL and Python for data engineering; PySpark experience strongly preferred.
Working knowledge of data modeling principles, including dimensional modeling and medallion architecture (bronze/silver/gold).
Experience integrating enterprise source systems into modern data platforms; ERP integration experience required (SAP preferred; Microsoft Dynamics GP a plus).
Understanding of data access controls, row-level security, and data classification within a governed enterprise platform.
Ability to translate business analytics and AI requirements into scalable, maintainable data platform solutions.
7–12 years of data engineering experience, including 3+ years of hands-on Databricks administration and pipeline development in an enterprise environment.
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field.

Nice To Haves

Experience with Databricks cost management, cluster optimization, and Azure billing analysis preferred.
Familiarity with regulatory data environments, including data governance requirements in FDA-regulated or ISO-certified manufacturing settings, preferred.
Experience with dbt (data build tool) or equivalent transformation frameworks a plus.
Manufacturing, healthcare, or life sciences data environment experience preferred.
Databricks Certified Data Engineer or equivalent Azure data certification preferred.

Responsibilities

Own and administer the AirLife Databricks environment end-to-end, including workspace management, Unity Catalog governance configuration, cluster lifecycle management, access control administration, and platform performance optimization.
Supervise staff including setting goals, mentoring staff, ensuring proper training and preparation for team assignments, and performance management
Design, build, and maintain scalable, reliable data pipelines that ingest, transform, and deliver data from AirLife's source systems — including SAP ECC, Microsoft Dynamics GP, Salesforce, and other operational platforms — into the Databricks Lakehouse in a governed, auditable manner.
Establish and enforce data governance standards across the Databricks platform, including data cataloging and discovery, metadata management, data lineage tracking, data quality rule definition and monitoring, and alignment with AirLife's master data standards.
Define, implement, and maintain AirLife's medallion data architecture (bronze/silver/gold or equivalent), ensuring that raw, cleansed, and business-ready datasets are clearly separated, documented, and fit for their intended consumption purpose.
Partner closely with the AI Lead, business analytics managers (Commercial Analytics, Supply Chain Analytics, Master Data), and FP&A to understand data consumption requirements and ensure the platform's structure, latency, and data quality meet both current and evolving business needs.
Monitor data pipeline health, platform performance, and data quality metrics on an ongoing basis; proactively identify, diagnose, and resolve issues before they impact downstream analytics or AI consumers.
Manage AirLife's commercial relationship with Databricks, including license governance, cost monitoring against budget (including Databricks spend currently embedded in Azure billing), and platform optimization to drive cost efficiency.
Define and document data engineering standards, pipeline development patterns, and platform runbooks to ensure the environment is maintainable, auditable, and capable of scaling with the team.
Lead data integration design reviews and support the evaluation of new data source onboarding, ensuring that integration patterns are consistent, governed, and aligned with the enterprise data architecture.
Contribute to AirLife's broader data and analytics strategy by providing technical input into architecture decisions, roadmap prioritization, and data capability development discussions led by the VP of Data, Analytics & AI.
Uphold and embody AirLife's values in all aspects of work.
Demonstrate accuracy and thoroughness in daily work; look for ways to improve and promote quality & safety.
Inspire the trust of others; treat people with respect and dignity and embrace the value of diversity.
Use time efficiently; perform job accurately, thoroughly, and conserve Company resources to improve profits.
Contribute to building and maintaining a positive team environment.
Assure all policies and guidelines are implemented and followed.