Data Platform & Governance Manager
First seen by Alion on Sep 24, 2026.
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).
Skills
Data Engineering, SQL, Python, Data Governance, Data Warehousing, Cloud, ETL, Database Architecture, Data Modeling