TJX - Data Platform & Governance Manager

Data Platform & Governance Manager

Role Type : Individual Contributor (IC)

Shift Timings : 2 : 30 PM - 11 : 30 PM - UK shift

Total Experience : 8-13 years

Ideal Candidate Persona :

We're seeking a Data & Analytics Solutions Manager (IC) who can combine analytics architecture, data engineering, governance, and business partnership to deliver trusted, scalable analytics solutions that enable data-driven decision-making across the enterprise.

Analytics Data Design & Enablement :

- Design and shape analytics-ready data models and structures (conceptual, logical, and dimensional) to support reporting, planning, and analytical use cases.

- Translate business requirements into clear analytics data needs, ensuring alignment with TJX-approved enterprise data platforms and architectures.

- Partner with TJX IT Data Architecture teams to ensure analytics models conform to enterprise standards while remaining flexible for evolving business needs.

- Establish reusable analytics patterns and templates that improve consistency, scalability, and time to insight across GBS.

Data Engineering Partnership & Pipeline Enablement :

- Work in close collaboration with TJX 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 to ensure pipelines effectively support reporting, dashboards, and advanced analytics.

- Support prioritization and design of data pipelines based on business value, data criticality, and analytics demand.

- Promote best practices in data reliability, observability, and performance from an analytics consumer perspective.

Data Quality, Governance & Compliance :

- Act as an analytics data steward, ensuring accuracy, consistency, and trustworthiness of analytics data assets.

- Partner with TJX IT Data Governance, Security, and Privacy teams to implement enterprise data policies, quality rules, and controls.

- Support data lineage, metadata management, certification, and issue remediation activities in alignment with TJX 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.

Business Intelligence & Reporting :

- Enable modern, governed BI solutions by defining semantic layers, KPIs, and reporting structures aligned with business priorities.

- Partner with analysts and product owners to ensure dashboards and insights are actionable, performant, and easy to consume.

- Support self-service analytics by promoting standardized, well-documented analytics datasets and definitions.

- Ensure BI and analytics outputs consistently reflect agreed data definitions and governance standards.

Advanced Analytics & AI Enablement :

- Knowledge of AI & Machine learning, Python libraries for data analytics.

- 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.

Technical Skills :

- Strong expertise in SQL, data modelling, and data warehouse / Lakehouse architecture.

- Hands-on experience with cloud data platforms (Azure, AWS, or GCP).

- Proven experience designing, developing, and maintaining ETL/ELT pipelines using modern analytics engineering tools such as dbt.

- Good knowledge of scheduling and orchestration tools (e.g., Control-M, Autosys, DAC, TAC, TMC).

- Strong programming and scripting skills (Python, SQL, Unix Shell Scripting, Stored Procedures).

- Experience with DevOps practices and CI/CD pipelines for data engineering.

- Strong BI architecture experience with tools such as Power BI, Tableau, or similar.

- Ability to create architecture diagrams, data flows, and technical design documentation.

- Understanding of Python libraries for data engineering and analytics; familiarity with ML/AI workflows and MLOps concepts.

Soft Skills :

- Excellent communication and stakeholder engagement skills.

- Strong analytical and problem-solving mindset.

- Ability to translate complex technical concepts into clear business outcomes.

- Strong influencing, mentoring, and cross-team collaboration capabilities.

Minimum Formal Education :

- Bachelor's degree in computer science, Information Systems, Engineering, or related discipline preferred (or equivalent experience).