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Tier-1 brand, mid-level data role in metro with broad skillset attracts high applicant competition.
Technical data engineering skills are transferable across industries, though banking compliance adds moderate domain bias.
Explicit 2+ years plus specific GCP, BigQuery, Spark, Kafka, and Python requirements enforce high shortlisting strictness.
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Participate in development of data warehouse table schemas across multiple databases within Technology and Data area.
Analyze data management challenges, independently guiding medium risk deliverables and recommending solutions for complex situations.
Collaborate with technology teams, internal partners, and stakeholders including internal and external customers to align data management efforts.
Minimum 2+ years of Data Engineering experience or equivalent through work, training, military experience, or education.
Proficiency with Python, SQL, and distributed processing frameworks like Apache Spark (Dataproc).
Experience with cloud data migration strategies and technologies (e.g., GCP, BigQuery, Bigtable).
Work Experience Required: 2+ years Data Engineering experience.
Experienced in designing and executing data migration from on-premises or legacy platforms to Google Cloud Platform services.
Skilled in implementing batch and streaming data pipelines using Cloud Composer (Airflow), Kafka, and Pub/Sub.
Proficient in building backend AI microservices, integrating APIs, and managing scalable ETL/ELT processes with databases such as MySQL, Hive, and MongoDB.