Staff Engineer - Data Engineering, Analytics & AI/ML

Overview

Staff Engineer for Data Engineering (primary), Analytics and AI/ML within the Global Merchandising Solutions Team, designing and optimizing enterprise data platforms, data integration solutions, ETL frameworks and analytics capabilities.

What you'll do

• 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.

What you'll need

• 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.
• Hands-on experience designing or developing data solutions using Snowflake and Databricks.
• Hands-on experience on any BI tool such as 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.

Nice to have

• Working experience with one or more additional ETL platforms, such as Informatica or IBM DataStage.
• 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.

Details

• Location: APAC Home Office, Hyderabad, IN (Salarpuria Sattva Knowledge City, Inorbit Road).