Lead Data Engineer Position
We are seeking an experienced professional to define and execute our data engineering strategy, driving the development of robust, scalable, and high-performance data infrastructure.
You will lead a team of data engineers, ensuring our data ecosystem meets the evolving needs of our enterprise data platform, APIs, advanced analytics, and other business requirements across the organization.
Ideal candidates bring deep technical expertise, a proven track record of building high-performing teams, and experience optimizing data solutions within an Azure Databricks environment.
You will collaborate closely with cross-functional stakeholders to ensure data initiatives align with broader business objectives, regulatory requirements, and best-in-class industry practices.
* Key Responsibilities:
o Develop and implement the vision, strategy, and roadmap for the enterprise data platform, ensuring alignment with overall business goals and seamless integration with other technological functions.
* Team Development:
o Recruit, mentor, and lead a high-performing team of data engineers, fostering a culture of continuous learning, innovation, and collaboration.
* Data Infrastructure:
o Build and maintain scalable data pipelines and infrastructure to power analytics, business intelligence, and delivery of data—optimizing for both efficiency and cost-effectiveness.
* Cross-Functional Collaboration:
o Partner with the architectural team, data strategy, data governance, data science, analytics, product management, and infrastructure teams across the global organization to design and implement solutions that maximize data's strategic value.
* Data Governance & Compliance:
o Ensure our enterprise data ecosystem maintains our standard controls for data governance, security, and compliance, ensuring adherence to frameworks like GDPR, HIPAA, and CCPA.
* Automation & Reliability:
o Drive automation in data processing and infrastructure management, implementing robust monitoring, alerting, and self-healing capabilities to enhance system reliability.
* Technology Evaluation:
o Continuously evaluate, select, and integrate new tools and technologies, ensuring the data engineering ecosystem remains state-of-the-art.
* Documentation & Enablement:
o Oversee the creation of comprehensive documentation, training materials, and knowledge-sharing resources to empower teams across the organization.
* Vendor & Stakeholder Management:
o Manage relationships with third-party vendors, performing technology assessments and ensuring optimal return on investment.
* Thought Leadership:
o Serve as an advocate for data-driven decision-making, championing the strategic value of data engineering and influencing stakeholders at all levels.