As a senior engineering leader, you will define and execute the data platform roadmap, partnering closely with architects, product management, data science, and infrastructure teams. You will guide and empower engineering teams to seamlessly integrate and deliver scalable, performant, and secure data capabilities on top of our Databricks lakehouse foundation. The ideal candidate combines technical depth in modern big data technologies with exceptional leadership, cross-functional collaboration, and operational excellence.
What you'll do:
Define and execute the data platform strategy and roadmap aligned with Flexera s business and product objectives.
Partner with architects and Principal Engineers to establish technical vision, architecture guardrails, and best practices for Databricks lakehouse implementations.
Lead and grow a team of engineers, fostering a culture of innovation, high performance, and continuous learning.
Drive platform scalability, reliability, governance, and cost efficiency, enabling analytics, AI/ML, and product innovation at scale.
Collaborate cross-functionally with Product, Analytics, Data Science, and Infrastructure to align priorities, define requirements, and ensure timely delivery of data capabilities.
Oversee the adoption and optimization of key technologies, including Databricks (Delta Lake, Unity Catalog, Photon, MLflow), orchestration frameworks, and streaming data patterns.
Champion data governance, security, and compliance by driving alignment with InfoSec, architecture, and legal stakeholders.
Manage budgets, cloud costs, vendor relationships, and resourcing to support platform growth and evolution.
Mentor and develop engineers and technical leaders, building deep expertise in Databricks internals, Spark optimization, and modern data architectures.
Define technical artifacts, including architecture diagrams, roadmaps, and best practice guides, to ensure clarity and alignment across teams.
Promote a high-standard engineering culture and operational excellence within the organization.
you'll be expected to have:
Bachelor s or higher degree in Computer Science, Software Engineering, or a related field.
15+ years of software engineering experience, with 8+ years building and operating large-scale data platforms.
5+ years in engineering leadership roles, including managing teams and leading cross-functional initiatives.
Expert-level proficiency with Databricks, including: Delta Lake internals (ACID transactions, time travel, data compaction strategies) Unity Catalog for data governance, security, and lineage Advanced Spark optimization and cluster management
Strong expertise with cloud-native data engineering in Azure or AWS, including storage (ADLS/S3), networking, and IAM integration.
Deep understanding of distributed systems, big data technologies, metadata catalogs, orchestration frameworks, and observability tooling.
Proven experience driving data governance, data modeling, and ontology initiatives to support analytics and AI/ML workflows.
Experience with streaming architectures (Apache Kafka, structured streaming), schema evolution, and event-driven data modeling.
Strong communication skills and emotional intelligence to collaborate effectively with diverse teams and stakeholders.
Demonstrated ability to mentor senior engineers, scale teams, and manage budgets and vendor relationships.
A continuous learner mindset actively keeping pace with evolving Databricks platform capabilities and broader data engineering trends.
Preferred but not required:
Experience with Power BI Direct Lake mode and semantic modeling for lakehouse-based analytics.
Familiarity with Mosaic AI, Databricks GenAI capabilities, or Feature Store implementations.
Contributions to open-source Spark, Databricks community content, or certifications (eg, Databricks Certified Data Engineer Professional).
Job Classification
Industry: IT Services & Consulting Functional Area / Department: Engineering - Software & QA Role Category: Software Development Role: Head - Engineering Employement Type: Full time