Senior Data Engineer

We are looking for a talented Senior Data Engineer to help build and enhance the data platform that supports analytics, operations, and data-driven decision-making across the organization. You will work hands-on to develop scalable data pipelines, improve data models, ensure data quality, and contribute to the continuous evolution of our modern data ecosystem.
 

You’ll collaborate closely with other Senior Engineers, Analysts, Data Scientists, and stakeholders across the business to deliver reliable, well-structured, and well-governed data solutions.
 

• Build, maintain, and optimize data pipelines for batch and streaming workloads.
• Develop reliable data models and transformations to support analytics, reporting, and operational use cases.
• Integrate new data sources, APIs, and event streams into the platform.
• Implement data quality checks, testing, documentation, and monitoring.
• Write clean, performant SQL and Python code.
• Contribute to improving performance, scalability, and cost-efficiency across the data platform.

• Work closely with other senior engineers and architects to implement architectural patterns and best practices.
• Collaborate with analysts and data scientists to translate requirements into technical solutions.
• Participate in code reviews, design discussions, and continuous improvement initiatives.
• Help maintain clear documentation of data flows, models, and processes.

• Support the adoption and roll-out of new data tools, standards, and workflows.
• Contribute to DataOps processes such as CI/CD, testing, and automation.
• Assist in monitoring pipeline health and resolving data-related issues.

• 6-10 years of experience as a Data Engineer or similar role.
• Hands-on experience with Snowflake (mandatory)—including SQL, modeling, and basic optimization.
• Strong knowledge of current arhitecure best practices of data pipelines and DWH.
• Experience with dbt (or similar)—model development, tests, documentation, and version control workflows.
• Strong SQL skills for data modeling and analysis.
• Proficiency with Python for pipeline development and automation.
• Experience working with orchestration tools (Airflow, Dagster, Prefect, or equivalent).
• Understanding of ETL/ELT design patterns, data lifecycle, and data modeling best practices.
• Familiarity with cloud environments (AWS, GCP, or Azure).
• Knowledge of data quality, observability, or monitoring concepts.
• Good communication skills and the ability to collaborate with cross-functional teams.
   

• Exposure to streaming/event technologies (Kafka, Kinesis, Pub/Sub).
• Experience with data governance or cataloging tools.
• Basic understanding of ML workflows or MLOps concepts.
• Experience with infrastructure-as-code tools (Terraform, CloudFormation).
• Familiarity with testing frameworks or data validation tools.

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.

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.

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.

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.

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.

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.