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Tier-1 employer and Bengaluru metro boost applicant density; specialized data lake skillset limits competition.
Data engineering and lake-platform skills are broadly transferable across industries.
Mandatory 7+ years and specific ETL/big-data/cloud skills make filters stringent.
Design, develop, and manage large-scale data ingestion, transformation, and analytics pipelines for structured, semi-structured, and unstructured data.
Build scalable and secure data lake platforms incorporating ETL/ELT frameworks to enable business insights with focus on data quality, performance, and governance.
Provide L2/L3 production support, optimize data pipelines for performance and cost efficiency, and collaborate with multiple teams for analytics enablement.
7+ years of experience in data engineering, ETL/ELT development, or data lake management.
Proficiency with ETL tools such as Informatica, Talend, dbt, or SSIS.
Hands-on experience with big data ecosystems (Hadoop, Spark, Hive, Presto, Delta Lake, or Iceberg) and cloud data platforms (AWS Glue, Redshift, Azure Synapse, GCP BigQuery).
Must be able to work onsite at HPE partner/customer office in India. Degree: Bachelor's or Master's in Computer Science, IT, or related field.
Experienced in building and optimizing large-scale data lake architectures supporting hybrid cloud environments.
Strong technical expertise in ETL/ELT pipeline design with real-time and batch data processing skills (e.g., Apache Spark, Kafka).
Comfortable with compliance/governance frameworks and capable of collaborating across analytics and cybersecurity teams to deliver enterprise-grade data solutions.