We're seeking a Senior Data Platform Engineer to join a team responsible for evaluating, validating, and enabling the adoption of emerging Microsoft and Databricks capabilities across the enterprise data platform ecosystem. This team serves as the technical governance and innovation function for platform engineering. New platform features, services, and tooling must be assessed, tested, and validated through proof-of-concepts before enterprise adoption. You will partner closely with platform teams to evaluate technologies such as Databricks Unity Catalog, Data Observability platforms, Databricks Genie, Zero Ops capabilities, and other emerging data platform innovations. The role combines hands-on engineering, platform integration, technical research, and advisory responsibilities.
Your Impact
- Evaluate new Microsoft Azure and Databricks platform capabilities and determine their suitability for enterprise adoption.
- Design and execute proof-of-concepts (POCs) to assess scalability, security, governance, operability, and business value.
- Build integrations and reusable frameworks leveraging APIs, platform services, and automation tooling.
- Collaborate with platform engineering teams to define technical standards, best practices, and adoption recommendations.
- Analyze emerging capabilities related to data governance, observability, AI-assisted operations, and platform automation.
- Develop technical documentation, decision frameworks, and architecture recommendations for stakeholders.
- Contribute to platform modernization initiatives by identifying opportunities to improve operational efficiency, reliability, and developer experience.
- Leverage AI-assisted engineering tools such as GitHub Copilot to accelerate experimentation and platform development.
Skills & Experience
- Strong hands-on experience with Databricks, including Unity Catalog and data governance concepts.
- Experience working with Azure Synapse Analytics and modern Azure data platform services.
- Solid background in API development, REST services, and system integrations.
- Experience integrating enterprise platforms, data services, and cloud-native solutions.
- Proficiency in one or more programming languages such as Python, Java, or Scala.
- Understanding of cloud architecture, automation, CI/CD practices, and source control using GitHub.
- Experience working in engineering teams conducting technical evaluations, pilots, or architectural assessments.
- Strong communication skills with the ability to present findings, risks, and recommendations to technical stakeholders.
Set Yourself Apart With
- Experience evaluating or implementing data observability platforms.
- Knowledge of Databricks Genie, AI-assisted analytics, or conversational data capabilities.
- Exposure to Zero Ops, platform automation, or self-service operational models.
- Experience with enterprise data governance, lineage, metadata management, and platform controls.
- Familiarity with AI-assisted software engineering using GitHub Copilot or similar coding assistants.
- Experience defining enterprise technology standards, governance frameworks, or platform approval processes.