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 or 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).
10+ years of hands-on experience in
ETL development
and
data engineering
.
Strong proficiency with tools:
IBM DataStage or Talend, Informatica, Databricks
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.

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