Overview
Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.We are seeking a Lead Data Engineer to design, build, and optimize enterprise-grade data pipelines and platforms that serve as the foundation for advanced analytics, reporting, and AI solutions. This role combines technical leadership, architecture oversight, and hands-on development, with a strong focus on quality, scalability, and stakeholder partnership.
Responsibilities
- Data Engineering
- Architect and implement data pipelines, data marts, and transformation layers using Snowflake as the primary cloud data platform.
- Develop and optimize ELT workflows with tools such as Matillion, dbt, or custom Python-based frameworks.
- Design Snowflake schemas, manage data modeling (star/snowflake) and performance tuning of queries, warehouses, and storage.
- Technical Leadership
- Set technical standards and provide leadership in building modular, reusable data engineering components in Snowflake.
- Lead code reviews, mentor data engineers, and guide development on CI/CD pipelines, version control, and Snowflake DevOps.
- Own the implementation of multi-environment Snowflake development frameworks for dev/test/prod promotion and change control.
- Platform Optimization & Monitoring
- Implement and monitor Resource Monitors, Query Profiles, and Warehouse auto-scaling to optimize cost and performance.
- Establish usage reporting, job monitoring, and error alerting using Snowflake native capabilities and integrated observability tools.
- Governance, Security, and Data Quality
- Define and enforce role-based access control (RBAC), data masking, and secure data sharing within and across domains.
- Support the implementation of data contracts, lineage, and data quality frameworks (e.g., Great Expectations).
- Collaborate with Data Governance teams to align platform use with compliance and policy requirements.
- Business Partnership & Collaboration
- Engage with product owners, analysts, and data scientists to deliver trusted, high-performance datasets.
- Translate business requirements into technical Snowflake data solutions.
- Serve as a Snowflake Data SME for cross-functional teams and stakeholders.
Qualifications
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
Required
- 10+ years of experience in data engineering, with 3+ years of hands-on work in Snowflake.
- Proficiency in SQL and Python, especially for ELT orchestration and automation.
- Expertise in data modeling (dimensional, normalized), warehouse optimization, and multi-cluster Snowflake configuration.
- Experience with modern ELT tools like Matillion, dbt, or similar.
- Familiarity with CI/CD practices, Git, and Snowflake-specific DevOps practices.
Preferred
- Snowflake SnowPro Certification (Core or Advanced).
- Experience integrating Snowflake with Salesforce, Oracle ERP, or other SaaS/enterprise systems.
- Exposure to cataloging tools (e.g., Alation, Collibra), Airflow, and monitoring platforms.
- Knowledge of cost governance and Snowflake usage optimization strategies.