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TJX

Runs off-price clothing and home goods stores

Data Platform & Governance Manager - Individual Contributor

Data ManagementConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listed

About the Job

Requirements

  • Bachelor’s degree in computer science, Information Systems, Engineering, or a related discipline is preferred, or equivalent experience.
  • At least 6 years of experience in data architecture, data engineering, analytics engineering, or related disciplines.
  • Demonstrated experience designing enterprise-scale analytics solutions in a cloud environment.
  • Strong expertise in SQL, data modelling, and data warehouse or Lakehouse architecture.
  • Hands-on experience with cloud data platforms such as Azure, AWS, or GCP.
  • Proven experience designing, developing, and maintaining ETL/ELT pipelines using dbt or similar tools.
  • Knowledge of scheduling and orchestration tools such as Control-M, Autosys, DAC, TAC, or TMC.
  • Strong programming and scripting skills in Python, SQL, Unix shell scripting, and stored procedures.
  • Experience with DevOps practices and CI/CD pipelines for data engineering.
  • Strong BI architecture experience with tools such as Power BI or Tableau.
  • Ability to create architecture diagrams, data flows, and technical design documentation.
  • Understanding of Python libraries for data engineering and analytics, and familiarity with machine-learning and AI workflows and MLOps concepts.
  • Excellent communication and stakeholder engagement skills.
  • Strong analytical and problem-solving skills.
  • Ability to translate complex technical concepts into clear business outcomes.
  • Strong influencing, mentoring, and cross-team collaboration capabilities.

Responsibilities

  • Design and shape analytics-ready conceptual, logical, and dimensional data models and structures for reporting, planning, and analytical use cases.
  • Translate business requirements into analytics data needs aligned with approved enterprise data platforms and architectures.
  • Partner with IT Data Architecture teams to ensure analytics models conform to enterprise standards while accommodating evolving business needs.
  • Establish reusable analytics patterns and templates to improve consistency, scalability, and time to insight across GBS.
  • Collaborate with IT Data Engineering and Platform teams to enable reliable ingestion, transformation, and orchestration of analytics data.
  • Provide analytics-domain input into ETL/ELT design decisions so pipelines support reporting, dashboards, and advanced analytics.
  • Support prioritization and design of data pipelines based on business value, data criticality, and analytics demand.
  • Promote data reliability, observability, and performance best practices from an analytics consumer perspective.
  • Act as an analytics data steward, ensuring the accuracy, consistency, and trustworthiness of analytics data assets.
  • Partner with Data Governance, Security, and Privacy teams to implement enterprise data policies, quality rules, and controls.
  • Support data lineage, metadata management, certification, and issue remediation in alignment with governance frameworks.
  • Embed data quality and governance requirements into analytics design, delivery, and ongoing monitoring processes.
  • Ensure analytics solutions comply with enterprise standards for data access, role-based security, and regulatory requirements.
  • Define semantic layers, KPIs, and reporting structures aligned with business priorities to enable governed BI solutions.
  • Partner with analysts and product owners to ensure dashboards and insights are actionable, performant, and easy to consume.
  • Promote self-service analytics through standardized, well-documented analytics datasets and definitions.
  • Ensure BI and analytics outputs reflect agreed data definitions and governance standards.
  • Design feature stores, model-serving layers, and MLOps pipelines where relevant.
  • Evaluate data readiness and infrastructure for advanced analytics use cases.
  • Promote adoption of AI-driven insights and analytical innovation across the organization.
  • Serve as a liaison between business teams and IT to establish shared understanding of requirements, constraints, and approvals.
  • Communicate analytics data concepts, trade-offs, and implications in clear, non-technical language.
  • Present analytics solutions, data quality considerations, and delivery approaches to stakeholders and leadership.
  • Build relationships that reinforce compliance, collaboration, and shared ownership of outcomes.
  • Apply architectural principles, coding standards, and analytics best practices when designing and delivering analytics solutions.
  • Participate in design reviews, performance evaluations, and technical assessments to ensure alignment with enterprise standards and quality expectations.
  • Partner with enterprise architecture and platform teams to evaluate tools, technologies, and patterns relevant to analytics use cases.
  • Support adoption and effective use of approved cloud-native analytics platforms and modern data stack practices.
  • Independently design and recommend data and analytics architecture solutions.
  • Make decisions on data modelling approaches, integration patterns, and platform usage within established enterprise guidelines.
  • Evaluate trade-offs between scalability, cost, performance, and delivery speed.
  • Influence technology and tooling decisions across the analytics landscape.
  • Provide architectural leadership and technical direction across multiple teams and initiatives.
  • Mentor and guide analysts, data engineers, and developers through influence rather than formal authority.
  • Own the architectural integrity of enterprise analytics platforms and data assets.
  • Enable multiple business domains through scalable, reusable analytics solutions and support data-driven decision-making across GBS and wider TJX stakeholders.

Desired Qualifications

  • Experience working with global teams and complex data landscapes.

About the Company

TJX

Runs off-price clothing and home goods stores

TJX runs off-price stores that sell brand-name clothing, shoes, accessories and home goods for less than department stores and malls charge, in the United States and abroad. Its best-known U.S. chains are T.J. Maxx, Marshalls and HomeGoods, which shoppers visit often because each store's mix of labels and products changes from week to week. Instead of ordering fixed seasonal collections, its buyers purchase closeouts, canceled orders and excess production directly from brands, and TJX makes money by reselling those goods at markdowns while keeping its own buying costs low. TJX was founded in 1987 and is headquartered in Framingham, Massachusetts.

Company size
10,001+
Company stage
IPO
Headquarters
Framingham, MA
Founded
1987

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