Lead Data Analyst

Target; Bengaluru; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Target is seeking a Lead Data Analyst for its IT Data Platform Analytics team in India. You will transform technology data into predictive insights and AI-enabled solutions, partnering with senior leaders to prioritize work and deliver measurable outcomes.

You will guide analytics frameworks, validate data requirements, and drive adoption of GenAI capabilities across technology domains. Strong communication and coaching skills are essential.

Qualifications

• SQL, data warehousing, and DW/BI concepts required.
• Experience with large, complex datasets and multiple sources.
• Hands-on with Python, R, or similar languages.

Responsibilities

• Lead data analyses that enable faster, smarter decision-making.
• Collaborate with senior technology leaders to frame problems and deliver analytics products.
• Develop AI-enabled analytical capabilities and predictive insights.
• Mentor analysts and raise analytical standards.

Skills

SQL proficiency

Data warehousing

BI visualization tools

Python / R

GenAI / AI concepts

Stakeholder storytelling

BigQuery / Spark

Airflow

Leadership

Education

B.Tech / B.E. or Masters in Statistics/ Econometrics/ Mathematics

Tools

GCP BigQuery

Spark

SQL warehouses

Airflow

Looker / Power BI / Tableau

Job description

About UsWorking at Target means helping all families discover the joy of everyday life.

About UsWorking at Target means helping all families discover the joy of everyday life.
About TargetAs a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact.
At Target, we have a timeless purpose and a proven strategy. Some of the best minds from different backgrounds come together to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. Target in India operates as a fully integrated part of Target's global team and supports the company's global strategy and operations.
About The TeamThe IT Data Platform (ITDP) team enables data-driven management of Target's technology ecosystem by bringing together trusted data and insights across technology assets, software delivery, infrastructure, reliability, security, engineering effectiveness, and technology operations. The Analytics team within ITDP transforms this data into metrics, analytical products, dashboards, predictive insights, and decision-support capabilities that help technology teams understand what is happening, why it is happening, where risk may be emerging, and where action is needed. The team is building towards an analytics capability that progresses from descriptive and diagnostic analytics to predictive and prescriptive insights, using statistical methods, applied data science, and GenAI where each approach is appropriate.
As a Lead Data Analyst for Target's IT Data Platform Analytics team you'll:Support Target Technology leadership with critical data analysis and intelligence that enables faster, smarter and more scalable decision-making across the technology ecosystem. Collaborate with senior stakeholders to understand priorities and roadmap, frame ambiguous problems, and turn technology data into analytical products, predictive capabilities, and AI-enabled solutions that achieve measurable outcomes.

• Demonstrated thought leadership in the application of data, analytics, data science, and AI to complex technology problems.
• Ability to work independently and with senior technology leaders to turn ambiguous problems into clear analytical questions, measurement frameworks, data solutions, models, and decision capabilities.
• Understand and articulate interfaces with Target Technology representatives, Product Managers, engineers, and other stakeholders to validate analytical requirements and present final results.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail, accuracy, and sound analytical judgment.
• Consult, design, develop, and deliver analytical solutions and AI (GenAI, Agent, Agentic) resulting in decision support, predictive insights, risk models, or reusable analytical capabilities.
• Expert in working with large-scale datasets using tools such as GCP BigQuery, Spark, or SQL-based warehouses and data pipelines using Airflow or similar tools.
• Practical experience to evaluate and monitor AI-driven analytical workflows, including defining quality metrics such as accuracy and relevance, assessing reliability, measuring business impact, and establishing appropriate evaluation practices.
• Lead the development and evolution of analytical frameworks such as Change Risk Score, predictive alerting, technology health signals, and other proactive intelligence capabilities, including methodology, validation, monitoring, and adoption.
• Connect signals across software delivery, applications, infrastructure, incidents, reliability, security, ownership, dependencies, and other technology domains to discover patterns and drivers that are not visible through isolated metrics.
• Develop expertise in technology domain context and cultivate trusted relationships with technology and product leaders; be a strong storyteller using data to influence decisions.
• Contribute to and establish the right artifacts to document AI solutions, analytical methodologies, model assumptions, evaluation approaches, and responsible-use considerations used in analytical projects.
• Contribute to knowledge-sharing systems, mentor analysts, and raise analytical standards through reusable methods, reviews, learning forums, and iterative model-building practices.
• Ensure compliance with corporate data protection standards and establish responsible AI practices, including data privacy, bias mitigation, explainability, governance, and appropriate risk considerations for analytical and AI-driven solutions.
• Keep up to date on technology analytics, applied data science, GenAI, agentic AI, and emerging methodologies, and identify high-value opportunities to apply them across ITDP.

About YouExperience: Overall 8-12 years exp and relevant 6-8 years exp
Qualification: B.Tech / B.E. or Masters in Statistics /Econometrics/Mathematics equivalent

• Adept at Structured Query Language (SQL), SQL optimization, data warehousing, and DW/BI concepts.
• Proficient in BI visualization tools (i.e. Looker, Power BI, Tableau) with ability to learn additional vendor and proprietary visualization tools.
• Expert in structured and unstructured data environments with proven hands-on work with large, complex datasets and multiple data sources.
• Hands-on experience in R, Python, or other open-source languages and analytical environments.
• Technical proficiency in analytical techniques such as Regression, Time-series models, Classification, Forecasting, Anomaly Detection, and similar methods to discover and measure key technology drivers and risks.
• Ability to evaluate statistical and machine-learning approaches, assess model performance and calibration, understand uncertainty and limitations, and translate models into actionable decision capabilities.
• Git source code management and experience working in an agile environment.
• Systematic and logical approach to problem-solving, with strong critical thinking and ability to navigate ambiguity and cross-domain dependencies.
• Highly self-motivated with a strong sense of urgency and ability to work independently and in team settings in a fast-paced environment; capability to manage urgent timelines.
• Ability and desire to teach, mentor, learn, and raise analytical capability across a broader team and stakeholder community.
• Excellent communication, service orientation, executive storytelling, and strong relationship-building skills; ability to influence technical and non-technical stakeholders.
• Identify and drive high-impact Generative AI (GenAI) opportunities by translating technology problems into scalable AI-enabled solutions that deliver measurable outcomes, including hands-on experience with LLMs, RAG, structured outputs, embeddings, or related techniques.
• Drive adoption of AI-agent enabled and agentic AI capabilities, enabling intelligent automation and embedding AI into enterprise analytical processes to enable faster decision-making.
• Establish and promote best practices for responsible and scalable AI adoption, including evaluation, governance, risk considerations, privacy, explainability, and integration with data and analytics ecosystems.

Useful Links- Life at Target- https://india.target.com/
Benefits- https://india.target.com/life-at-target/workplace/benefits