L. B. Nagar Hyderabad Telangana Data & analytics solutions manager Jobs – 765 Open Jobs Today

Data & Analytics Solutions Manager
TJX Companies —Hyderabad, Telangana
- Full-time
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Data & Analytics Solutions Manager

TJX Companies -
Hyderabad, Telangana

Apply Now

Job details

Full-time
14 days ago

Qualifications

BCS
CI/CD
Power BI
Data modelling
Azure
Management
Business intelligence
Computer Science
DevOps
UNIX
Information Systems
Tableau
SQL
AWS
Analysis skills
Bachelor's degree
Machine learning
Continuous integration
Scripting
ETL
AI
Communication skills
Python
Shell Scripting
Control-M
Analytics

Full job description

TJX Companies

At TJX Companies, every day brings new opportunities for growth, exploration, and achievement. You’ll be part of our vibrant team that embraces diversity, fosters collaboration, and prioritizes your development. Whether you’re working in our four global Home Offices, Distribution Centers or Retail Stores—TJ Maxx, Marshalls, Homegoods, Homesense, Sierra, Winners, and TK Maxx, you’ll find abundant opportunities to learn, thrive, and make an impact. Come join our TJX family—a Fortune 100 company and the world’s leading off-price retailer.

Job Description:

Title: Data & Analytics Solutions Manager

Role Type - Individual Contributor (IC)

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

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 (Business‑Facing)

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.

Stakeholder Management & Communication

Serve as a key liaison between business teams and TJX IT, ensuring shared understanding of requirements, constraints, and approvals.
Communicate analytics data concepts, tradeoffs, and implications in clear, non‑technical language.
Present analytics solutions, data quality considerations, and delivery approaches to stakeholders and leadership.
Build trusted relationships that reinforce compliance, collaboration, and shared ownership of outcomes.

Technical Leadership & Best Practices

Apply and adhere to TJX‑defined 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 new 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.

Decision Making

Independently designs and recommends data and analytics architecture solutions.
Makes decisions on data modelling approaches, integration patterns, and platform usage within established enterprise guidelines.
Evaluates trade-offs between scalability, cost, performance, and delivery speed.
Influences technology and tooling decisions across the analytics landscape.

Span of Control (i.e. Direct/Indirect reports)

Individual contributor role with no direct people management responsibility.
Provides architectural leadership and technical direction across multiple teams and initiatives.
Mentors and guides analysts, data engineers, and developers through influence rather than formal authority.

Scope of Responsibility (i.e. financial impact)

Owns the architectural integrity of enterprise analytics platforms and data assets.
Impacts multiple business domains through scalable, reusable analytics solutions.
Plays a critical role in enabling data-driven decision making across GBS and wider TJX stakeholders.

Skills/Knowledge

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 (or similar).
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).

Minimum Experience

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.
Experience working with global teams and complex data landscapes preferred.

In addition to our open door policy and supportive work environment, we also strive to provide a competitive salary and benefits package. TJX considers all applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, gender identity and expression, marital or military status, or based on any individual's status in any group or class protected by applicable federal, state, or local law. TJX also provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law.

Address:

Salarpuria Sattva Knowledge City, Inorbit Road

Location:

APAC Home Office Hyderabad IN

Apply Now

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Explore jobs in more locations

Title: Data & Analytics Solutions Manager

Role Type - Individual Contributor (IC)

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

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 (Business‑Facing)

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.

Stakeholder Management & Communication

Serve as a key liaison between business teams and TJX IT, ensuring shared understanding of requirements, constraints, and approvals.

Communicate analytics data concepts, tradeoffs, and implications in clear, non‑technical language.

Present analytics solutions, data quality considerations, and delivery approaches to stakeholders and leadership.

Build trusted relationships that reinforce compliance, collaboration, and shared ownership of outcomes.

Technical Leadership & Best Practices

Apply and adhere to TJX‑defined 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 new 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.

Decision Making

Independently designs and recommends data and analytics architecture solutions.

Makes decisions on data modelling approaches, integration patterns, and platform usage within established enterprise guidelines.

Evaluates trade-offs between scalability, cost, performance, and delivery speed.

Influences technology and tooling decisions across the analytics landscape.

Span of Control (i.e. Direct/Indirect reports)

Individual contributor role with no direct people management responsibility.

Provides architectural leadership and technical direction across multiple teams and initiatives.

Mentors and guides analysts, data engineers, and developers through influence rather than formal authority.

Scope of Responsibility (i.e. financial impact)

Owns the architectural integrity of enterprise analytics platforms and data assets.

Impacts multiple business domains through scalable, reusable analytics solutions.

Plays a critical role in enabling data-driven decision making across GBS and wider TJX stakeholders.

Skills/Knowledge

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 (or similar).

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).

Minimum Experience

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.

Experience working with global teams and complex data landscapes preferred.