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Staff Engineer - Data Engineering, Analytics & AI/ML

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Design and maintain enterprise ETL/ELT pipelines, primarily in Talend

  • Design data solutions on Snowflake and Databricks with governance and cost in mind

  • Build warehouse and dimensional data models for analytics needs

  • Lead design and code reviews, troubleshooting and performance tuning

  • Mentor junior ETL developers and data engineers

From the employer’s posting
Design, develop, and maintain enterprise ETL/ELT pipelines using Talend as the primary integration platform
Design and implement modern data solutions using Snowflake and Databricks, applying platform best practices for performance, security, governance, scalability, and cost efficiency
Develop data warehouse solutions and dimensional, relational, and analytical data models that meet evolving business and analytics requirements
Lead technical design reviews, code reviews, troubleshooting, root-cause analysis, performance tuning, and production-readiness activities
Mentor junior ETL developers and data engineers

What you’ll bring

All qualifications

Core experience

  • Bachelor's Degree in Computer Science, Information Technology, Engineering, Analytics, or a related field and 9+ years of relevant experience in Data Engineering, ETL development, Data Warehousing, Data Modelling or related disciplines.
  • Strong expertise in Data Warehousing, dimensional modeling, relational data modeling, and enterprise data architecture.
  • Hands-on experience designing or developing data solutions using Snowflake and Databricks.
  • Hands on experience on any BI tool like Power BI , Tableau , Cognos etc
  • Experience with workload scheduling and orchestration tools such as Control-M, AutoSys, DAC, TAC, TMC, or equivalent technologies.
  • Knowledge of DevOps practices, source control, automated testing, and CI/CD implementation for data pipelines and database deployments.

Preferred experience

  • Experience with Microsoft Azure data technologies such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, or related services.
  • Experience supporting enterprise Business Intelligence, Analytics, Data Science, Machine Learning, AI, or GenAI solutions.
  • Knowledge of data governance, metadata management, data lineage, data quality, master data management, and access-control practices.
  • Understanding of modern lakehouse architectures, medallion design patterns, distributed data processing, and cloud data platform modernization.
Qualification wording
Bachelor's Degree in Computer Science, Information Technology, Engineering, Analytics, or a related field and 9+ years of relevant experience in Data Engineering, ETL development, Data Warehousing, Data Modelling or related disciplines.
Strong expertise in Data Warehousing, dimensional modeling, relational data modeling, and enterprise data architecture.
Hands-on experience designing or developing data solutions using Snowflake and Databricks.
Hands on experience on any BI tool like Power BI , Tableau , Cognos etc
Experience with workload scheduling and orchestration tools such as Control-M, AutoSys, DAC, TAC, TMC, or equivalent technologies.
Knowledge of DevOps practices, source control, automated testing, and CI/CD implementation for data pipelines and database deployments.
Experience with Microsoft Azure data technologies such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, or related services.
Experience supporting enterprise Business Intelligence, Analytics, Data Science, Machine Learning, AI, or GenAI solutions.
Knowledge of data governance, metadata management, data lineage, data quality, master data management, and access-control practices.
Understanding of modern lakehouse architectures, medallion design patterns, distributed data processing, and cloud data platform modernization.
Education & alternatives
Minimum Qualifications - Bachelor's Degree in Computer Science, Information Technology, Engineering, Analytics, or a related field and 9+ years of relevant experience in Data Engineering, ETL development, Data Warehousing, Data Modelling or related disciplines. - Extensive hands-on experience designing, developing, and supporting enterprise data integration and ETL/ELT solutions.
Apply at TJX Companies

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 3, 20261 day ago
Recorded sightings
1
Last seen by us
Nov 4, 2026
Employer says posted
Oct 26, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

TJX Companies is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Shell
  • SQL
  • Azure
  • Databricks
  • Power BI
  • Snowflake
  • Tableau
Where the posting names them
- Create architecture and solution design documents, data flow diagrams, interface specifications, and detailed technical specifications. - Develop engineering solutions using Python, SQL, Unix shell scripting, stored procedures, and related database programming techniques. - Implement and improve scheduling and orchestration using tools such as Control-M, AutoSys, DAC, TAC, TMC, or comparable platforms.
- Hands on experience on any BI tool like Power BI , Tableau , Cognos etc - Programming and scripting experience using Python, SQL, Unix shell scripting, and stored procedures. - Experience with workload scheduling and orchestration tools such as Control-M, AutoSys, DAC, TAC, TMC, or equivalent technologies.
- Develop data warehouse solutions and dimensional, relational, and analytical data models that meet evolving business and analytics requirements. - Write and optimize advanced SQL queries, SQL scripts, stored procedures, ETL jobs, batch processes, and large-scale data workloads. - Create architecture and solution design documents, data flow diagrams, interface specifications, and detailed technical specifications.
- Extensive hands-on experience designing, developing, and supporting enterprise data integration and ETL/ELT solutions. - Expert-level SQL skills, including complex query development, SQL script optimization, execution-plan analysis, performance tuning, stored procedures, and database programming. - Strong expertise in Data Warehousing, dimensional modeling, relational data modeling, and enterprise data architecture.
Preferred Qualifications - Experience with Microsoft Azure data technologies such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, or related services. - Experience supporting enterprise Business Intelligence, Analytics, Data Science, Machine Learning, AI, or GenAI solutions.
- Design, develop, and maintain enterprise ETL/ELT pipelines using Talend as the primary integration platform, with experience in Informatica and IBM DataStage. - Design and implement modern data solutions using Snowflake and Databricks, applying platform best practices for performance, security, governance, scalability, and cost efficiency. - Develop data warehouse solutions and dimensional, relational, and analytical data models that meet evolving business and analytics requirements.
- Working experience with one or more additional ETL platforms, such as Informatica or IBM DataStage will be good to have. - Hands-on experience designing or developing data solutions using Snowflake and Databricks. - Hands on experience on any BI tool like Power BI , Tableau , Cognos etc
- Hands-on experience designing or developing data solutions using Snowflake and Databricks. - Hands on experience on any BI tool like Power BI , Tableau , Cognos etc - Programming and scripting experience using Python, SQL, Unix shell scripting, and stored procedures.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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:

Staff Engineer


What you’ll discover

  • Inclusive culture and career growth opportunities
  • A truly Global IT Organization that collaborates across North America, Europe, Asia and Australia, click here to learn more
  • Challenging, collaborative, and team-based environment

What you’ll do

The Global Merchandising Solutions Team is responsible for managing various merchandising, analytics, and distribution-related solutions within TJX IT. The organization delivers capabilities that enrich our internal customer experience and provide core business value. We are seeking an experienced and hands-on Staff Engineer, Data Engineering(primary), Analytics and AI/ML, who will play a key role in designing, developing, modernizing, and optimizing enterprise data platforms, data integration solutions, ETL frameworks, and analytics capabilities. The Staff Engineer will partner effectively with product teams, architects, business partners, and cross-functional engineering teams to deliver scalable, reliable, and secure data solutions while fostering an inclusive culture and growth mindset.


What you’ll need

The Global Merchandising Solutions Team thrives on strong relationships with our business partners and works diligently to address their needs while supporting TJX growth and operational stability. On this tightly knit and fast-paced solution delivery team, you will be challenged to think creatively, solve complex engineering problems, and drive technical excellence.

  • Design, develop, and optimize scalable data integration solutions that support enterprise analytics, reporting, and AI/ML use cases.
  • Provide extensive hands-on technical expertise for data engineering initiatives and guide teams in delivering reliable, maintainable, and high-performing solutions.
  • Shape, evaluate, and redesign existing data architecture, data models, and integration frameworks to improve scalability, performance, resilience, and maintainability.
  • Design, develop, and maintain enterprise ETL/ELT pipelines using Talend as the primary integration platform, with experience in Informatica and IBM DataStage.
  • Design and implement modern data solutions using Snowflake and Databricks, applying platform best practices for performance, security, governance, scalability, and cost efficiency.
  • Develop data warehouse solutions and dimensional, relational, and analytical data models that meet evolving business and analytics requirements.
  • Write and optimize advanced SQL queries, SQL scripts, stored procedures, ETL jobs, batch processes, and large-scale data workloads.
  • Create architecture and solution design documents, data flow diagrams, interface specifications, and detailed technical specifications.
  • Develop engineering solutions using Python, SQL, Unix shell scripting, stored procedures, and related database programming techniques.
  • Implement and improve scheduling and orchestration using tools such as Control-M, AutoSys, DAC, TAC, TMC, or comparable platforms.
  • Apply DevOps practices and CI/CD automation to data pipelines, database changes, ETL code, testing, and deployments.
  • Collaborate with Product Owners, Architects, Analytics teams, AI/ML teams, business partners, and other Data Engineering teams to deliver end-to-end solutions.
  • Enable analytics, Data Science, Machine Learning, and GenAI initiatives by providing high-quality, governed, scalable, and trusted data foundations.
  • Lead technical design reviews, code reviews, troubleshooting, root-cause analysis, performance tuning, and production-readiness activities.
  • Mentor junior ETL developers and data engineers, promote engineering standards, and foster knowledge sharing and continuous improvement.
  • Communicate complex technical concepts clearly and effectively to technical and non-technical stakeholders.
  • Demonstrate a solution-oriented mindset, strong ownership, adaptability, and the ability to quickly learn new technologies and business domains.

 

Minimum Qualifications

  • Bachelor's Degree in Computer Science, Information Technology, Engineering, Analytics, or a related field and 9+ years of relevant experience in Data Engineering, ETL development, Data Warehousing, Data Modelling or related disciplines.
  • Extensive hands-on experience designing, developing, and supporting enterprise data integration and ETL/ELT solutions.
  • Expert-level SQL skills, including complex query development, SQL script optimization, execution-plan analysis, performance tuning, stored procedures, and database programming.
  • Strong expertise in Data Warehousing, dimensional modeling, relational data modeling, and enterprise data architecture.
  • Deep hands-on experience with Talend, including ETL pipeline design, development, optimization, scheduling, monitoring, troubleshooting, and production support.
  • Working experience with one or more additional ETL platforms, such as Informatica or IBM DataStage will be good to have.
  • Hands-on experience designing or developing data solutions using Snowflake and Databricks.
  • Hands on experience on any BI tool like Power BI , Tableau , Cognos etc
  • Programming and scripting experience using Python, SQL, Unix shell scripting, and stored procedures.
  • Experience with workload scheduling and orchestration tools such as Control-M, AutoSys, DAC, TAC, TMC, or equivalent technologies.
  • Knowledge of DevOps practices, source control, automated testing, and CI/CD implementation for data pipelines and database deployments.
  • Experience producing architecture documents, solution designs, data flows, technical specifications, and operational support documentation.
  • Strong analytical, troubleshooting, and problem-solving capabilities across complex and data-intensive environments.
  • Proven ability to lead technical delivery, influence engineering decisions, and mentor ETL developers and data engineers.
  • Strong written and verbal communication skills with the ability to work effectively across engineering, architecture, product, and business teams.
  • Self-motivated, collaborative, and solution oriented, with a growth mindset and commitment to continuous learning.

Preferred Qualifications

  • Experience with Microsoft Azure data technologies such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, or related services.
  • Experience supporting enterprise Business Intelligence, Analytics, Data Science, Machine Learning, AI, or GenAI solutions.
  • Knowledge of data governance, metadata management, data lineage, data quality, master data management, and access-control practices.
  • Understanding of modern lakehouse architectures, medallion design patterns, distributed data processing, and cloud data platform modernization.
  • Experience implementing monitoring, observability, alerting, and DataOps practices for enterprise data pipelines and platforms.
  • Experience working with data systems across cloud, hybrid, and multiple operating-system environments.
  • Experience in retail, merchandising, supply chain, or another large-scale enterprise analytics environment is a strong plus.
  • Strong business acumen and the ability to connect technical solutions with measurable business outcomes.
  • Advanced degree in Computer Science, Data Engineering, Analytics, AI, Distributed Computing, or a related field is a plus.

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

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Location & working pattern

Hyderabad, Telangāna, India

- Experience implementing monitoring, observability, alerting, and DataOps practices for enterprise data pipelines and platforms. - Experience working with data systems across cloud, hybrid, and multiple operating-system environments. - Experience in retail, merchandising, supply chain, or another large-scale enterprise analytics environment is a strong plus.
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