Manager Data Analytics and Solutions

Area: EM (Asia-Pacific) | Global Sales

Department: e-commerce

Direct Reporting Line: Senior Manager, Digital Analytics & Solutions, EM e-com

Secondary reporting line: Sr Director, Planning and Analytics EM e-com

Subsidiary/country: EM Hub

Location: Gurugram (India)

GSMS Grade: M4

Number of Personnel Managed: -

Cost Center/Budget and/or Revenue Responsibility: EM

Purpose & Overall Relevance for the Organization:

Candidate will be responsible for managing and executing data engineering and implementing analytics solutions across Consumer Engagement, Competitor Intelligence, and Experience Analytics & Automation functions. This role will involve leading the development of data pipelines, creating data products, ensuring data availability for Power BI reports, and driving new automation initiatives to enhance operational efficiency. The ideal candidate will possess strong technical expertise, leadership skills, and a proven track record of managing data engineering projects that drive business impact.

Key Responsibilities:

Data Engineering and Development:

• Databricks Development: Lead the development and management of data products and dashboards on the Databricks platform, ensuring robust data processing and analytics capabilities.
• Pipeline Creation: Design, build, and maintain data pipelines through CICD that ensure seamless data flow from various systems into the analytics environment.
• Data Availability for Power BI: Ensure that all necessary data is available and up-to-date for Power BI reports, including creating and managing the necessary pipelines.
• Data Product Development: Develop data products tailored to the specific needs of the Consumer Engagement, Competitor Intelligence, and Experience Analytics teams.
• Responsible for tools and systems daily routines & activities, refresh, updates and scheduling.

Dashboard Management and Development

• Dashboard Transition: Oversee the smooth transition of existing dashboards to the new data architecture, ensuring minimal disruption and data consistency.
• New Dashboard Solutions: Collaborate with business stakeholders to gather requirements and develop new dashboard solutions that meet their analytical needs.
• CX Clickstream Integration: Integrate Customer Experience (CX) clickstream data into new reports, ensuring alignment with global definitions and standards.
• Membership KPIs Reporting: Lead efforts to develop comprehensive reports on membership KPIs, supporting the Consumer Engagement team.
• Maintain quality, set good development practices, and define standards that keep the focus on the right things.

Automation Initiatives

• Report Automation: Lead efforts to automate recurring reports, reducing manual effort and improving accuracy and timeliness.
• PPT Automation: Develop automation solutions for PowerPoint presentations, streamlining the process of generating and updating slides with the latest data.

Quality Assurance and Best Practices

• Data Quality Assurance: Implement rigorous quality checks and monitoring to ensure the accuracy and reliability of data within pipelines and dashboards.
• Best Practices: Advocate for and implement best practices in data engineering, analytics development, and stakeholder management to drive efficiency and effectiveness.

Collaboration and Leadership

• Team Collaboration: Work closely with data engineers, analysts, and BI developers to ensure cohesive and integrated solutions across functions.
• Mentorship: Provide guidance and support to junior team members, fostering a culture of learning and continuous improvement within the Data Solutions team.
• Cross-Functional Engagement: Collaborate with IT, marketing, finance, and other departments to ensure that data solutions align with broader business objectives.

Databricks Migration

• Migration Planning: Outline detailed plans for migrating existing jobs and Dashboards to Databricks, including timelines, resource allocation, and risk management strategies.
• Execution: Execute the migration by identifying dependencies, updating existing data sources, ensuring compatibility with the new environment, and performing quality control.

Stakeholder Engagement

• Requirements Gathering: Work closely with business stakeholders to understand their needs, translating them into technical requirements and actionable development plans.
• Continuous Communication: Maintain regular communication with stakeholders to provide updates on project progress, gather feedback, and adjust plans as necessary.
• Build a strong internal and external network, assorbing from the adidas Digital Analytics community the latest trends and technological advances.

Key Relationships:

• EM Hub e-com team
• EM Function teams (Finance, DNA, Brand, Sales, SCM…)
• Country-Clusters (C/C) e-commerce teams
• Country-Clusters (C/C) market teams & group functions
• Global Data Digital teams
• Global BI & Analytics teams
• External vendors

Requisite Education and Experience / Minimum Qualifications:

• 5-7 years of experience of experience in data engineering, with at least 2 years in a managerial role.
• Strong expertise in Databricks, Power BI, and data pipeline development.
• Experience with dashboard development and transition in a large-scale enterprise environment.