HP Enterprise—AI/ML Data Engineer

Job description

Description: AI/ML Data Engineer This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE 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: At HPE Networking, the Digital Experience & Automation (DEA) team is reimagining how people experience support and services in a digital‑first world - setting new standards for the future of networking. We enable customers, partners, and employees through AI‑driven tools and modern platforms, transforming support into a unified, efficient, and simple experience that drives measurable value. Our mission is grounded in innovation with purpose: applying automation, AI, and data‑driven insights to simplify journeys, reduce friction, and create meaningful outcomes at every touchpoint. DEA’s charter is to discover, evaluate, and scale solutions that embed intelligent technology into every interaction - delivering proactive and predictive experiences that shorten resolution times and accelerate task completion. By modernizing processes and accelerating self‑service, we help shift support from reactive to truly anticipatory. We partner closely with technology providers, engineering, and business teams to deliver seamless omnichannel experiences and enable business transformation through data engineering, process optimization, and automation. Our work is fueled by a passion for self‑service, intelligent automation, and building digital experiences that are intuitive, scalable, and human‑centric. What you'll do: Responsibilities: Develop, maintain, and optimize data pipelines and workflows and Feature Store to ensure seamless data ingestion and transformation as a scalable data solution. - Design, develop, implement, and architect Data Engineering pipelines, considering performance & scalability including data storage and processing. - Implement advanced data transformations and quality checks to ensure data accuracy, completeness, security and consistency of data. - Seamlessly integrate data from diverse sources, for data ingestion, transformation and storage, leveraging AWS S3 Storage and possibly Snowflake as a SQL Data Warehouse. - Create and implement advanced data models and schemas and ensure data governance and data management best practices. What you need to bring: Qualification and Desired Experiences: - 5+ years of data analysis and engineering experience - Bachelor’s degree in computer science, Statistics, Informatics, Information Systems or another quantitative field. - Working knowledge of API or Stream-based data extraction processes like Salesforce API and Bulk API and have hands-on experience in web crawling. Primary Tech skills: - Advanced Web-crawling & scraping methods and tools - Building end-end Data Engineering pipelines for Semi and unstructured data (Text, all kinds of simple/complex table structures, images, video and audio data) - Python, Pyspark, SQL, RDBMS - Data Transformation (ETL/ELT) activities - SQL Data warehouse (e.g. Snowflake) working / preferably administration Secondary Tech skills: - Databricks - Familiarity with AWS services : S3, Glue, EMR, EC2, RDS, monitoring and IAM - Kafka, Spark & Kafka Streaming - Workflow automation (e.g. using Github actions) - Performing RCA Personal Skills: - Ability to collaborate cross-functionally and build sound working relationships within all levels of the organization - Ability to handle sensitive information with keen attention to detail and accuracy. Passion for data handling ethics. - Effective time management skills and ability to solve complex technical problems with creative solutions while anticipating stakeholder needs and helping meet or exceed expectations - Comfortable with ambiguity and uncertainty of change when assessing needs for stakeholders - Self-motivated and innovative; confident when working independently, but an excellent team player with a growth-oriented personality Accessibility HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here. Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability. 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 #networking Job: EngineeringJob 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: python, sql, data engineering, data pipeline development, data transformation, etl, data warehousing, snowflake, rdbms, pyspark, data modeling, data governance, api integration, web crawling, data quality assurance, aws s3, data storage, data security, databricks, aws glue, aws emr, aws ec2, aws rds, kafka, spark, kafka streaming, workflow automation, github actions, data ethics, cross-functional collaboration