HP Enterprise—Data Lake SME

Job description

Description: Data Lake SME This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE partner/customer office. Who We Are: 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. Job Description: 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. Key Responsibilities - 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 Science, IT, or related field. - Preferred certifications: - AWS Certified Data Analytics – Specialty / Azure Data Engineer Associate / GCP Data Engineer. - Informatica/Talend/dbt certifications (nice to have). What We Can Offer You: Health & Wellbeing We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing. Personal & Professional Development We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division. Unconditional Inclusion We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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. Let's Stay Connected: Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE. #india #operations Job: ServicesJob Level: TCP_03 HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity. Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities. HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories. Recruitment Fraud Alert We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications. All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately. Skills: data lake architecture, etl development, data lake management, sql, python, data governance, data quality management, etl/elt frameworks, apache spark, apache hadoop, data integration, data pipeline optimization, data security, data lineage management, metadata management, apache kafka, apache flink, data cataloging, partitioning, indexing, caching, workflow orchestration, airflow, aws glue, redshift, azure synapse, gcp bigquery, informatica, talend, dbt