Sr. Manager Data Analytics-1

Job Id: R0000450354

About us:

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.

Working at Target means the opportunity to help all families discover the joy of everyday life. Caring for our communities is woven into who we are, and we invest in the places we collectively live, work and play. We prioritize relationships, fuel and develop talent by creating growth opportunities, and succeed as one Target team. At our core, our purpose is ingrained in who we are, what we value, and how we work. It’s how we care, grow, and win together.

A role in Merchandising Capabilities means partnering with Merchandising, technology, data science and analytics leaders to co-create solutions that maximizes business value and enables key strategies that are critical to the enterprise and for the experiences we create for our guests. Truly an owner and expert of your product and underlying processes, you will set the vision, align on the roadmap and mobilize teams to deliver needed outcomes. Given most strategies have a business impact, you will also serve as a trusted resource to guide other enterprise partners in their solutions to ensure the success and integrity of end-to-end deliverables.

As a Sr. Manager, Data Analytics in Merchandising, you will be accountable for setting the vision, strategy, roadmap, and quality expectations for data, reporting, analytics, automation, and AI capabilities for a specific business function within our Merchandising organization. You will serve as an advocate of our data-driven culture and a trusted advisor to business leaders, helping identify where analytics and AI can create the greatest business value. In partnership with your team of Data Analysts, you will translate business priorities into a portfolio of scalable solutions, ensure measurable outcomes, and build an effective analytics ecosystem that informs and influences decisions. You will build a high-performing team through talent pipeline planning, hiring, coaching, setting clear expectations, capability development, and performance management. You will partner closely with Merchandising, Product Management, Data Science, Technology, and other analytics teams to align solutions, address capability gaps, and democratize trusted data and insights.

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

As a Sr. Manager, Data Analytics for Target's Merch Data Analytics team you'll:

Lead an analytics team that supports our world-class Merchandising leadership with data, insights, automation, and AI capabilities that enable faster, smarter, and more scalable decision-making. Collaborate with stakeholders to understand their priorities and roadmaps, translate business problems into a clear portfolio of work, and hold the team accountable for delivering measurable business outcomes.

• Set the vision, strategy, and roadmap for data, reporting, analytics, automation, and AI capabilities for the business area, and prioritize work based on business value, urgency, scalability, and strategic alignment.
• Provide thought leadership in the application of data and analytics, helping business leaders identify opportunities where insights, automation, Generative AI, AI agents, or agentic AI can materially improve decisions and outcomes.
• Translate complex and ambiguous business problems into a portfolio of scalable analytical and AI-enabled solutions, defining clear success measures and ensuring the team remains focused on business outcomes rather than isolated technical deliverables.
• Guide and challenge the team's analytical and solution-design approach, establishing expectations for technical quality, scalability, maintainability, and appropriate use of statistical, analytical, and AI methods.
• Ensure the team has the capability to work effectively with large-scale datasets and modern data ecosystems, including platforms and technologies such as GCP BigQuery, Spark, SQL-based data warehouses, and data pipelines using Airflow or similar orchestration tools.
• Establish standards for evaluating and monitoring AI-driven analytical workflows, including defining appropriate quality metrics such as accuracy and relevance, assessing reliability, and measuring adoption and business impact of AI-enabled solutions.
• Identify and prioritize high-impact Generative AI opportunities and guide the adoption of AI-agent-enabled and agentic AI capabilities to automate repeatable analytical work, improve productivity, accelerate insight generation, and enable faster decision-making.
• Establish and promote responsible and scalable AI practices, including data privacy, governance, bias and risk considerations, explainability, human oversight, and integration with the broader data and analytics ecosystem.
• Ensure analytical methodologies, AI solutions, key assumptions, evaluation approaches, and reusable patterns are appropriately documented to improve transparency, maintainability, knowledge sharing, and reuse across the team.
• Partner closely with Merchandising, Product Management, Data Science, Technology, and analytics partners to align roadmaps, resolve dependencies, identify capability gaps, and democratize access to trusted data and insights.
• Develop trusted relationships with business leaders and communicate complex analytical and technical concepts in clear business terms, ensuring recommendations are actionable and connected to measurable business drivers.
• Build and lead a high-performing team of approximately 8-10 analysts through talent pipeline planning, hiring, onboarding, coaching, performance management, succession planning, and career development.
• Develop both business acumen and technical capability within the team, fostering a culture of critical thinking, curiosity, experimentation, teaching, learning, collaboration, and continuous improvement.
• Ensure adherence to corporate information protection and data governance standards across analytical and AI-enabled solutions.
• Stay current on industry trends, best practices, emerging analytical methodologies, modern data platforms, Generative AI, AI agents, and agentic AI, and determine where they can create meaningful value for Target.

About you:

• Undergraduate Degree in Information Technology, Computer Science, Data Science, Applied Mathematics, Statistics, or related quantitative discipline, or equivalent work experience.
• Minimum of 12 years of experience in data analytics or related disciplines and a minimum of 2 years of people management experience.
• Demonstrated experience leading analytics teams, setting direction and priorities, and delivering analytical solutions that influence meaningful business decisions.
• Strong ability to translate business strategy and ambiguous problems into an actionable analytics roadmap and to manage trade-offs across competing priorities and initiatives.
• Strong technical fluency across SQL, data warehousing and BI concepts, large-scale data environments, and visualization platforms such as Power BI, Looker, Tableau, or equivalent tools; able to review, challenge, and guide technical approaches without being the primary hands-on executor.
• Strong understanding of modern data platforms and analytical ecosystems, including technologies such as GCP BigQuery, Spark, SQL-based warehouses, and workflow orchestration or data pipelines such as Airflow.
• Working knowledge of analytical programming environments such as Python, R, Hive, or similar languages, along with strong conceptual understanding of analytical techniques such as regression, time-series analysis, classification, experimentation, and other methods used to identify and measure business drivers.
• Experience guiding teams in the use of Generative AI and LLM-based solutions, including prompt engineering, Retrieval-Augmented Generation (RAG), AI-assisted analytical workflows, AI agents, and agentic AI capabilities.
• Ability to assess AI-enabled solutions through appropriate measures of quality, reliability, relevance, adoption, and business impact, and to establish responsible AI practices including privacy, governance, bias and risk considerations, and explainability.
• Understanding of software development and analytical engineering practices including Git source code management, reusable development patterns, documentation, and Agile ways of working.
• Strong problem-solving and critical-thinking skills, attention to detail, and ability to manage ambiguity and urgency in a fast-paced environment.
• Excellent communication, storytelling, service orientation, and relationship-building skills, with the ability to influence senior stakeholders and translate technical concepts into business implications and recommendations.
• Demonstrated ability to hire, coach, develop, and retain analytical talent and to build an environment that supports accountability, learning, knowledge sharing, and career growth.
• Experience with Retail, Merchandising, or Marketing is a strong add-on.

Useful Links-

Life at Target- https://india.target.com/

Benefits- https://india.target.com/life-at-target/workplace/benefits

Culture- https://india.target.com/life-at-target/diversity-and-inclusion