About the role 

We are seeking a seasoned Data Engineering SME with strong experience in data platforms, ETL tools, and cloud technologies. The ideal candidate will lead the design and implementation of enterprise-scale data solutions, provide strategic guidance on data architecture, and play a key role in data migration, data quality, and performance tuning initiatives. This role demands a mix of deep technical expertise, project management, and stakeholder communication.
 

Key Responsibilities

Lead the design, development, and deployment of robust, scalable ETL pipelines and data solutions. Provide technical leadership and SME support for data engineering teams across multiple projects. Collaborate with cross-functional teams including Data Analysts, BI Developers, Product Owners, and IT to gather requirements and deliver data products. Design and optimize data workflows using tools such as IBM DataStage, Talend, Informatica, and Databricks. Implement data integration solutions for structured and unstructured data across on-premise and cloud platforms. Conduct performance tuning and optimization of ETL jobs and SQL queries. Oversee data quality checks, data governance compliance, and PII data protection strategies. Support and mentor team members on data engineering best practices and agile methodologies. Analyze and resolve production issues in a timely manner. Contribute to enterprise-wide data transformation strategies including legacy-to-digital migration using Spark, Hadoop, and cloud platforms. Manage stakeholder communications and provide regular status reports.
 

Required Skills and Qualifications

Bachelor's degree in Engineering, Computer Science, or a related field (MTech in Data Science is a plus). 8+ years of hands-on experience in ETL development and data engineering. Strong proficiency with tools: IBM DataStage, Talend, Informatica, Databricks, Power BI, Tableau. Strong SQL, PL/I, Python, and Unix Shell scripting skills. Experience with cloud platforms like AWS and modern big data tools like Hadoop, Spark. Solid understanding of data warehousing, data modeling, and data migration practices. Experience working in Agile/Scrum environments. Excellent problem-solving, communication, and team collaboration skills. Scrum Master or Product Owner certifications (CSM, CSPO) are a plus.