PNE Data Foundations Sr. Lead at Mars
Verden (Aller), Niedersachsen, Germany -
Full Time


Start Date

Immediate

Expiry Date

09 Jun, 25

Salary

0.0

Posted On

10 Mar, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

JOB DESCRIPTION:

The PNE Data Foundations Sr Lead ensures that Pet Nutrition Europe (PNE) has a strong, governed, and scalable data foundation to enable high-quality analytics and insights. This role is critical in bridging the gap between the AOE D&A data team and PNE, ensuring alignment with global data models, governance principles, and strategic data initiatives such as the DDF (Digital Data Foundation) program.

Responsibilities
  • Data Governance & Compliance: Ensure all PNE data assets follow the governance frameworks, data quality standards, and security policies defined by the AOE D&A data team.
  • Data Model & Architecture Alignment: Ensure that analytics solutions within PNE fully leverage the data models, governance structures, and best practices established at the AOE level.
  • Data Engineering & Infrastructure: Oversee the design, development, and maintenance of data pipelines, integrations, and ETL processes to ensure efficient data flow and accessibility for analytics use cases.
  • Collaboration & Stakeholder Management: Act as the key connection between AOE D&A and PNE, facilitating knowledge-sharing, alignment, and implementation of strategic data initiatives, including the DDF program.
  • Data Platform Optimization: Work closely with AOE data teams and PNE analytics teams to optimize the data infrastructure, ensuring performance, scalability, and cost efficiency.
  • Metadata & Asset Management: Drive consistent metadata management and data asset governance, ensuring data reliability, accessibility, and standardization across PNE.
  • Enablement & Best Practices: Educate and support the PNE teams in data stewardship best practices, ensuring they effectively leverage governed data assets and self-service capabilities.
  • Monitoring & Data Quality Assurance: Implement data validation, lineage tracking, and anomaly detection mechanisms to ensure high data quality across PNE analytics initiatives.
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