Staff Engineer

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.