Sr. Analyst Data Foundations (Mumbai)

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 whats next. Overview The Senior Data Analyst Data Foundations will play a pivotal role in shaping and advancing our data ecosystem. This role requires a blend of technical expertise, analytical curiosity, and business partnership, working closely with leaders, D&T; peers, and global stakeholders to deliver scalable, high-quality data solutions. You will serve as a technical data subject matter expert, guiding data best practices, mentoring analysts, and ensuring that our data products are governed, reliable, and impactful. This role is ideal for someone who thrives at the intersection of business insight, data engineering, and analyticsand who is eager to contribute to General Mills digital transformation journey. Key Accountabilities Partner with business SMEs, D&T; peers, and Solution Managers to understand data needs and align Data Foundations with enterprise DnA strategy Build strong understanding of DnA Cloud technology and connect current Data Foundation capabilities with future-state solutions Gather and analyze business requirements, translating them into transparent technical specifications, delivery plans, and actionable data solutions Communicate timelines, priorities, and progress with stakeholders to ensure alignment, transparency, and timely delivery Serve as a lead analyst and technical SME, providing coaching, mentorship, and oversight to analysts within the Data Foundations team Partner with data engineers, analytic engineers, and architects to design, build, maintain, and optimize scalable, high-quality data pipelines on GCP Define and promote best practices in data analysis, data modeling, documentation, governance, metadata, and lineage standards Use observability and monitoring tools such as Monte Carlo and Collibra to improve data reliability, trust, and quality Drive innovation through automation, AI enablement, knowledge-sharing, and capability-building initiatives that strengthen analytical maturity Support sustainability and compliance goals by building and maintaining data models and pipelines for reporting, regulatory needs, and real-time analytics Minimum Qualifications Bachelors or masters degree in Computer Science, Information Systems, Software Engineering, or a related quantitative field 10+ years of overall IT or IT-enabled services experience, including 7+ years in data analytics or data analysis roles Strong SQL skills with hands-on experience in ETL processes, data modeling, data pipelines, and data transformation tools Strong analytical ability to translate complex data into actionable insights that support business decisions Good business understanding with the ability to connect data work to business needs and outcomes Excellent verbal and written communication skills, with the ability to simplify complex ideas and collaborate across global, cross-functional teams Strong understanding of agile methodologies and collaborative delivery practices Positive, proactive, and self-driven mindset with strong ownership and commitment to team success Preferred Qualifications FMCG exposure: Broad understanding of commercial marketing, planning, sourcing, manufacturing, logistics, and sustainability, and how data enables insights across these domains. Agile and product delivery: Experience delivering solutions in an agile or Scrum environment, with a focus on iterative development, stakeholder feedback, and continuous improvement. Leadership and mentoring: Ability to coach and mentor junior analysts, facilitate peer reviews, and promote knowledge sharing across global teams. Stakeholder management: Strong relationship management and collaboration skills, with proven success working with business and technical leaders across regions. Analytical innovation: Interest in exploring AI, GenAI, or automation to enhance data quality, analyst productivity, and insight generation. Academic and professional excellence: Strong academic background and continuous-learning mindset, demonstrated through certifications, courses, or hands-on learning in emerging data technologies. ELIGIBILITY Applicants must meet minimum age qualifications in the country in which the job is located. .