Data Lake SME

Data Lake SME This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE partner/customer office.

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

HPE Operations is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you. What you’ll do: We are looking for an experienced Data Lake / ETL Engineer with 7+ years of expertise in designing, developing, and managing large-scale data ingestion, transformation, and analytics pipelines . The role involves building scalable and secure data lake platforms, enabling business insights through efficient ETL/ELT frameworks, and ensuring data quality, performance, and governance across the enterprise ecosystem.

Data Lake Architecture & Development Design and implement data ingestion pipelines for structured, semi-structured, and unstructured data . Develop and manage ETL/ELT processes for large-scale data processing. Optimize storage and retrieval strategies across on-prem and cloud-based data lakes. Data Integration & Processing Integrate data from multiple sources (databases, APIs, streaming platforms). Implement real-time and batch processing using Apache Spark, Kafka, or Flink . Support metadata management, data lineage, and cataloging. Performance & Optimization Tune queries and pipelines for high performance and cost efficiency. Implement partitioning, indexing, and caching strategies for large datasets. Automate routine ETL/ELT workflows for reliability and speed. Security & Governance Ensure compliance with data governance, privacy, and regulatory standards (GDPR, HIPAA, etc.). Implement encryption, masking, and role-based access control (RBAC). Collaborate with cybersecurity teams to align with Zero Trust and IAM policies. Collaboration & Support Partner with data scientists, analysts, and application teams for analytics enablement. Provide L2/L3 support for production pipelines and troubleshoot failures. Mentor junior engineers and contribute to best practices documentation. Required Skills & Experience 7+ years of experience in data engineering, ETL/ELT development, or data lake management . Strong expertise in ETL tools (Informatica, Talend, dbt, SSIS, or similar). Hands-on experience with big data ecosystems : Hadoop, Spark, Hive, Presto, Delta Lake, or Iceberg. Proficiency with SQL, Python, or Scala for data processing and transformation. Experience with cloud data platforms (AWS Glue, Redshift, Azure Synapse, GCP BigQuery). Familiarity with workflow orchestration tools (Airflow, Temporal, Oozie). Preferred Knowledge Exposure to real-time data streaming (Kafka, Kinesis, Pulsar). Knowledge of data modeling (Kimball/Inmon), star schema, and dimensional modeling . Experience with containerized deployments (Docker, Kubernetes). What you need to bring: Bachelor’s or Master’s degree in Computer