Design, develop, and maintain
ETL pipelines using IBM DataStage (CP4D)
and
AWS Glue/Lambda
for ingestion from varied sources like flat files, APIs, Oracle, DB2, etc.
Build and optimize data flows for loading curated datasets into
Snowflake
, leveraging best practices for schema design, partitioning, and transformation logic.
Participate in
code reviews
, performance tuning, and defect triage sessions.
Work closely with data governance teams to ensure
lineage, privacy tagging, and quality controls
are embedded within pipelines.
Contribute to
CI/CD integration
of ETL components using Git, Jenkins, and parameterized job configurations.
Troubleshoot and resolve issues in QA/UAT/Production environments as needed.
Adhere to agile delivery practices, sprint planning, and documentation requirements.

Required Skills and Experience

4+ years
of experience in ETL development with at least
1–2 years in IBM DataStage (preferably CP4D version)
.
Hands-on experience with
AWS Glue
(PySpark or Spark) and
AWS Lambda
for event-based processing.
Experience working with
Snowflake
: loading strategies, stream tasks, zero-copy cloning, and performance tuning.
Proficiency in
SQL
,
Unix scripting
, and basic
Python
for data handling or automation.
Familiarity with
S3
, version control systems (Git), and job orchestration tools.
Experience with
data profiling, cleansing, and quality validation
routines.
Understanding of
data lake/data warehouse architectures
and DevOps practices.

Good to Have

Experience with
Collibra, BigID
, or other metadata/governance tools
Exposure to
Data Mesh/Data Domain models
Experience with agile/Scrum delivery and Jira/Confluence tools
AWS or Snowflake certification is a plus

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