Description
We are seeking a Senior Data Engineer to join our Global Customer Experience Analytics team within HPE's Networking Business Unit. As a Senior Data Engineer, you will design and build scalable data pipelines, integrate complex data sources, and enable high-quality analytics across the organization.
Responsibilities:
- Partner with cross-functional teams to identify opportunities for data-driven improvements and translate business needs into technical solutions.
- Ingest and integrate data from structured and unstructured enterprise systems, including Databricks and IT data platforms.
- Design and build curated data models and analytical layers to support reporting and downstream analytics.
- Develop, optimize, and maintain pipelines using SQL, Python, and orchestration tools.
- Clean, transform, and prepare datasets for reliable consumption across the business.
- Ensure data quality and observability across pipelines, workflows, and storage layers.
- Integrate new data sources, APIs, and event streams into the platform.
- Create clear data documentation and communicate technical concepts to non-technical stakeholders.
- Stay current with modern data engineering tools, cloud technologies, and best practices.
Requirements:
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field.
- 9+ years of experience in data engineering or related domains.
- Strong proficiency in SQL and relational database technologies.
- Advanced Python skills for pipelines, automation, and testing.
- Deep understanding of ETL/ELT patterns, data modeling, and data lifecycle management.
- Hands-on experience with orchestration tools (Airflow, Dagster, Prefect, etc.).
- Knowledge of data quality, observability, and monitoring frameworks.
- Experience with CI/CD, DataOps, and automation practices.
- Familiarity with data governance and compliance.
- Experience with Databricks, Alteryx, and BI tools such as Power BI or Tableau (for data consumption enablement).
- Experience with cloud storage and distributed systems (AWS S3, Hadoop, Hive, Snowflake).
- Familiarity with major cloud platforms (AWS, GCP, Azure).
- Ability to manage multiple projects, prioritize effectively, and work independently or collaboratively.
- Strong communication skills with the ability to translate technical concepts into business-friendly language.