As part of our Cloud Data Platform team, you will be a key contributor in the build and management of our cloud native data platforms and tools.
You will leverage your expertise in cloud native technologies to ensure adherence to best practices, that platform usage is optimized, and capabilities are being leveraged in line with our strategic vision.
Your team will establish, enforce, and monitor frameworks for our data products and self-service data environments. You will work with cross functional partners to design flexible, scalable frameworks, security controls, and architecture patterns across our data platforms.
Finally, your team will define, manage, and support our emerging DevOps framework and processes, managing the tooling, monitoring data engineering and development work, and ensuring that development and deployment is done following leading industry best practices.
Functional Capabilities :
Ability to understand and synthesize complex concepts and problems into simple, reusable, scalable, and elegant solutions.
Flexible and open mindset : Sees challenges and problems as opportunities to grow. Understands there are multiple ways to solve a problem, respects and listens to multiple opinions, and continuously evaluates and challenges assumptions.
Strategic Thinking : Aligns strategy of the solution with overall company and department goals.
Strong communications skills to collaborate with the virtual global team
Pragmatic approach to deliver incremental value to the organization
Comfortable operating within a global, complex, highly matrixed organization
Strong problem solving and analytical skills
Technical Competencies :
Detailed conceptual and technical understanding of building data capabilities in a cloud native environment. Experience on Azure preferred, with focus on building serverless architectures.
Expertise in data platforms (Data Lake, Data Warehousing, Graph DB, NoSQL, etc.) and integration ingestion patterns (ETL, ELT, API, streaming, etc.)
Understanding of Data as a Service concepts including APIs / web services and microservices
Experience in defining semantic and / or virtualization layers, metadata to support technical and business teams for development and data consumption
Expert in SQL, PySpark, and / or Python
Strong understanding of data modeling concepts; hands-on data modeling expertise desired (preferably in ERwin)
Demonstrated experience in architecting and implementing an end to end modern cloud data stack at scale in a complex Retail or CPG organizations.
Beauty industry experience a plus.
Mastery of relational databases, enterprise data lakes, cloud data warehouse platforms, NoSQL, and ETL / ELT data integration technologies.
Azure and Snowflake experience preferred.
Expertise in visualization and reporting tools and modern AI / ML platforms
Experience in establishing tooling and frameworks for supporting DevOps and CI / CD pipelines
Familiarity with building and managing APIs to enable data as a service and data virtualization technologies a plus
Ability to establish and maintain collaborative relationships with technical, analytic, and non-analytic business partners, including executive leadership.
Bachelor’s degree in Engineering, Mathematics, Information Systems or related field.