Manager - Data Engineering

通用磨坊股份有限公司; Mumbai; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

General Mills' Enterprise Data Development team designs and architect solutions to transform business data into a scalable Data Warehouse using cloud technologies like GCP. You will mentor managers, align data initiatives with business priorities, and drive end-to-end data engineering programs at scale.

The role requires strong stakeholder collaboration across functions and geographies, a passion for data quality, and the ability to lead in a fast-paced, globally distributed environment.

Qualifications

• 15+ years of experience in data engineering.
• 5+ years leading mid-to-large data engineering teams.
• Strong stakeholder management across functions, geographies and time zones.
• Experience with cloud-based data platforms and modern data engineering environments.
• Experience working in Agile delivery or Product Team environments.

Responsibilities

• Directly manage, coach, and performance-manage a team of Data Engineering Managers.
• Build relationships with key business and technology stakeholders to communicate risk and opportunity.
• Translate data needs into actionable engineering initiatives.
• Drive a culture of learning, belonging, and accountability within the team.
• Oversee resource allocation and capacity planning for the Data Engineering group.
• Manage vendor relationships and contracts as needed.
• Lead initiatives to improve efficiency and the operating model of Data Engineering.

Skills

Data engineering

Stakeholder management

Agile delivery

Analytical thinking

People leadership

Tools

Google Cloud Platform (GCP)

ETL/ELT

Data Warehousing

Job description

COMPANY OVERVIEW

We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best - bold thinkers with big hearts who challenge one another and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what's next.

OVERVIEW

General Mills' Digital and Technology team is a large global function that drives technology innovation and digital transformation across the business. The team partners closely with business stakeholders to identify opportunities where technology can improve efficiency, create value, and enable disruption. Its capabilities span AI/ML, Data Science, IoT, NLP, Cloud, Infrastructure, RPA, Cyber Security, Blockchain, SAP S4 HANA, and Enterprise Architecture. Through the MillsWorks agile-at-scale model, business and technology teams work together in pods with a shared mission to deliver value. Employees contributing to major technology initiatives are seen as digital transformation change agents, and the team promotes an inclusive, learning-focused culture shaped by its "Work with Heart" philosophy and commitment to service, equity, and community impact.

Purpose of the role

The Enterprise Data Development team is responsible for designing & architecting solutions to integrate & transform business data into Data Warehouse to deliver data layer for the Enterprise using cutting edge cloud technologies like GCP. We design solutions to meet the expanding need for more and more internal/external information to be integrated with existing sources; research, implement and leverage new technologies to deliver more actionable insights to the enterprise. We integrate solutions that combine process, technology landscapes and business information from the core enterprise data sources that form our corporate information factory to provide end to end solutions for the business.

KEY ACCOUNTABILITIES

• Directly manage, coach, mentor, and performance manage a team of Data Engineering Managers, fostering a culture of learning, innovation, and collaboration.
• Build and maintain strong relationships with key business and technology stakeholders, ensuring effective communication regarding project status, risks, and opportunities.
• Collaborate with stakeholders to deeply understand their data needs and priorities, translating them into actionable data engineering initiatives.
• Champion a Data Engineering culture of Learning, Belonging, and Accountability, driving employee engagement and development initiatives.
• Oversee resource allocation and capacity planning for the Data Engineering team, working with project and solution managers to ensure appropriate staffing.
• Manage vendor relationships and contracts as needed, ensuring optimal value and alignment with Data Engineering goals.
• Identify and lead initiatives to improve the efficiency and effectiveness of the Data Engineering operating model, streamlining processes and automating tasks.
• Drive the adoption of best practices, standards, and data quality improvements across the Data Engineering team.
• Participate in the development and drive the implementation of short-term and long-term strategic initiatives for Data Engineering, ensuring alignment with business goals.
• Provide technical guidance and mentorship to the Data Engineering team, staying up-to-date on the latest trends and technologies, and contributing to the development of data architecture and standards.

MINIMUM QUALIFICATIONS

• 15+ years of relevant experience in Data Engineering, including 5+ years leading mid-to-large Data Engineering teams and managers
• Strong stakeholder management skills with the ability to influence and collaborate effectively across functions, geographies, and time zones
• Deep understanding of data engineering principles, practices, and technologies, backed by strong analytical and hands-on technical capability
• Proven experience working with cloud-based data platforms and modern data engineering environments
• Experience working in Agile delivery or Product Team environments, supported by strong communication and interpersonal skills

PREFERRED SKILLS/EXPERIENCES

• Data Engineering Expertise: Specialization in Google Cloud Platform (GCP).
• Big Data & Data Warehousing: Proficient in ETL/ELT processes and data architecture design.
• Project Management: Experienced in managing data engineering projects.

ELIGIBILITY

Applicants must meet minimum age qualifications in the country in which the job is located.