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Director, Data Platform Engineering Lead

Brand: Estée Lauder Companies

Description

The Director, Data Platform Engineering Lead is a key role to drive the technology blueprints and roadmaps of our Azure-based Data and Analytics platforms and solutions. The resource combines expert conceptual understanding of data engineering and data management with deep technical understanding of Cloud Provider services, with a strong focus on the Azure ecosystem. The Data Engineering Lead stays abreast with the latest development in the fast-evolving cloud space, has the ability to drive Proof of Concepts with internal teams and vendors, and clearly articulates the fit of potential solutions for capabilities needed by ELC. Additionally, as a strong collaborator with Enterprise Architecture, Security and Data Operations, the resource ensures adherence to ELC’s policies, standards and best practices, while considering implications for the operationalization of new capabilities and platforms.

Main responsibilities:

• Accountable for the end-to-end scalable technical architecture and engineering solutions for Data and Analytics platforms and services deployed on Azure

• Continuously evaluates platform capabilities required by Data Product consumers and Data Engineers; evaluates services and solutions by cloud providers, conducts Proof of Concepts and identifies best fit solutions in adherence with data governance, security and operations.

• Designs engineering patterns and develops reusable assets and frameworks to standardize solutions, automate processes, thereby reducing overall complexity and Total Cost of Ownership

• Collaborates with Network and Data Security to design appropriate controls to keep ELC’s data safe and in alignment with ECR data policies

• Conducts regular cadence with Platform team to identify any opportunities for cost reduction on provisioned Azure services

• Monitors and maintains system health, security setup and connectivity of all Azure services in Data and Analytics Azure platforms

• Defines and documents best practices and user guides for data engineers, consumers and support team

• Mentors data engineering teams by helping them with technical guidance on their day to day work

• Participate in technical interviews and workshops to support growth of the Data and Analytics program

Qualifications

Technical Skills and Qualifications:

Functional Capabilities:

• Enterprise Data Platform mindset: building standardized, optimized, available, reliable, consistent, accessible data platform to support the development and operations of data products

• Strategic Thinking: Aligns strategy of group with overall company goals and establishes objectives and assigns responsibilities.

• Strong problem solving and analytical skills

• Strong communications skills: collaborates with the virtual global data engineering teams to convey concepts and designs

• Results-driven: sets aggressive goals and delivers through the team

• Pragmatic approach to deliver incremental value to the organization

• Comfortable within a global, complex, highly matrixed organization

• Well-developed team management skills: ability to mentor team members, lead a team of engineers supporting Data Platform services enhancements

• Proven ability to attract, retain, and develop talent

• Ability to establish credibility and be decisive – but able to recognize and support the organization’s preferences and priorities.

Technical Competencies:

• Strong expertise and proven hands-on development experience with the Azure ecosystem for Data and Analytics organizations

• Expert understanding of Data Lake, Data Warehousing, ETL and ELT processes, and Data Quality frameworks

• Expert in conceptual and technical understanding of Big Data platforms, Data Lakes, Data Warehousing, their capabilities and applicable use cases and implications for developing data products on these types of platforms

• Expert understanding of Data as a Service concepts including APIs/web services and microservices

• Expertise in coding languages: python (must-have), pyspark (highly desired)

• Strong understanding of data consumption needs: defining semantic layers, metadata to support technical and business teams

• Strong understanding of Data Science and Machine Learning concepts(desired) and how to operationalize models in a data platform.

• Comfortable with agile development methodology (Scrum, Kanban) and supporting tools (e.g. Jira)

Leadership Competencies:

• Thinks Strategically: Takes a broad view of the business, industry, and consumer environment to anticipate and plan for the future. Identifies the focus and defines where to play, how to win and what capabilities and management systems are required.

• Develops Talent and Capabilities: Identifies and cultivates essential skills and attributes to maximize individual contribution and engagement.

• Demonstrates Learning Agility: Ability to anticipate change, face reality, draw conclusions, and swiftly mobilize to adapt to changing needs and demands.

• Drives Creativity and Innovation: Focuses on areas of highest potential. Creates newness or connects knowledge in new ways to create the unexpected. Ensures that the creativity and innovation pipeline are aligned to achieve strategy and goals.

• Strives for Excellence in Execution: Proactively seeks ways to improve personal and organizational effectiveness to meet current and future business needs. Learns equally from successes and failures.

Job: Information Technology

Primary Location: Europe, Middle East, Africa-RO-B-Bucharest

Job Type: Standard

Schedule: Full-time

Shift: 1st (Day) Shift

Job Number: 248231