We are seeking experienced Data Engineers who are passionate about innovation and thrive on tackling complex challenges. This position offers an exceptional opportunity to work on high-impact projects involving Data Engineering, AI/ML, and Generative AI within one of the most forward-thinking organizations in the tech industry.
As a Data Engineer, you will design, build, and optimize scalable data solutions that support HP's AI/ML initiatives. Collaborating closely with data scientists, data architects, and data product owners, you will create robust pipelines and frameworks to process and analyze massive datasets, enabling insightful and strategic decision-making.
Key Responsibilities
- Data Pipeline Development. Design, develop, and maintain efficient and scalable data pipelines and ETL processes using technologies like Python, SQL, Databricks, and Azure Data Factory.
- Data Processing and Optimization. Implement, optimize, and maintain complex SQL queries and Python scripts for high-performance data processing and analytics.
- Data Modeling and Architecture. Build and manage robust data models and architectures to ensure data quality, consistency, and optimal performance.
- Collaborative Problem Solving. Work closely with cross-functional teams, including data scientists and architects, to understand project requirements and deliver tailored data engineering solutions.
- Monitoring and Troubleshooting. Proactively monitor data pipelines to detect and resolve issues, ensuring data accuracy, reliability, and availability across systems.
- Global Team Coordination. Collaborate effectively with teams across multiple time zones, particularly in the Americas and Asia, to drive seamless execution and on-time delivery of projects.
- Continuous Learning. Stay abreast of the latest industry trends, technologies, and best practices to continuously improve data engineering workflows and capabilities.
Qualifications
Required Skills and Experience
Professional Experience
- 4-6 years of hands-on experience as a Data Engineer or in a similar technical role.
- Proven expertise in ETL processes, data processing, and programming with Python and SQL.
Technical Skills
- Extensive experience with Databricks and a solid understanding of Apache Spark for large-scale data processing.
- Hands-on experience with Azure Data Factory and building scalable data pipelines.
- Proficiency in data warehousing, data modeling, and designing data architectures.
Soft Skills
- Strong problem-solving skills to troubleshoot and resolve data-related challenges.
- Excellent communication and collaboration abilities for working with diverse, global teams.
- A proactive mindset with a strong willingness to learn and adopt new technologies.
Educational Background
- A Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field. Equivalent work experience or demonstrated expertise will also be considered.
Preferred Skills
- Experience with cloud platforms, especially Microsoft Azure.
- Familiarity with big data tools and technologies.
- Knowledge of data governance and security best practices.
- Understanding of Agile methodologies and DevOps practices.
- Awareness of cutting-edge technologies, including AI/ML and Generative AI.
Why Join Us?
HP offers a unique blend of exciting challenges, rewarding work, and continuous learning opportunities. As a Data Engineer in our team, you will benefit from.
- Access to Advanced Tools and Technologies. Collaborate on innovative projects using the latest tools in data engineering, AI/ML, and big data analytics.
- Professional Growth. Enhance your skills and advance your career in a collaborative and inclusive environment that encourages personal and professional development.
- Competitive Compensation and Benefits. Enjoy a market-competitive salary and comprehensive benefits package designed to support your well-being.
- Dynamic Work Environment. Thrive in a culture that values innovation, diversity, and teamwork, working alongside some of the brightest minds in the industry.
Join us at HP and contribute to shaping the future of data-driven innovation!