IT Engineer,Software,Advanced

Job Description

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 powerful, award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. Diversity, equity & inclusion are integral parts of our culture and drivers of innovation at Keysight. 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 with deep expertise in Snowflake and strong functional knowledge of Finance data to architect and deliver trusted, high-performing data products that support financial reporting, forecasting, planning, and compliance. In this role, you will work closely with Finance, FP&A, and Accounting teams to build pipelines and models that enable timely, data-driven decision-making. Responsibilities 1. Snowflake Platform & Pipeline Ownership Design and build robust ELT pipelines in Snowflake to integrate financial data from ERP systems (e.g., Oracle, SAP), billing platforms, and planning tools. Deliver clean, well-modeled financial data marts for P&L analysis, cash flow, variance analysis, forecasting, and budget tracking. Optimize Snowflake usage with efficient schema design, warehouse tuning, and compute/storage cost management. 2. Functional Partnership with Finance Teams Collaborate with Finance, FP&A, and Accounting stakeholders to understand business processes, reporting requirements, and data dependencies. Support financial reporting cycles (monthly close, audits, forecast submissions) by ensuring timely, reliable data pipelines. Translate complex financial logic such as allocations, consolidations, and time-based adjustments into scalable data transformations. 3. Data Governance, Quality & Controls Implement role-based access control, secure data zones, and masking policies to manage sensitive financial and employee data. Partner with Data Governance teams to maintain data dictionaries, financial definitions, lineage documentation, and audit trails. Apply rigorous data quality checks to ensure the integrity of financial metrics used in dashboards, planning models, and reports. 4. Technical Leadership & Best Practices Lead the adoption of modern data engineering frameworks using tools like dbt, Matillion, and CI/CD pipelines for Snowflake. Mentor junior engineers and analysts on SQL optimization, data modeling for finance, and best practices for code reuse and maintainability. Drive continuous improvement in pipeline reliability, monitoring, and performance tuning. 5. Integration Across Finance Tech Stack Integrate Snowflake with FP&A tools (e.g., Onestream) and BI/reporting platforms (e.g., Tableau, Power BI, Microstrategy). Build reusable financial data products that serve multiple use cases planning, tax, audit, compliance, and executive dashboards. Qualifications Careers Privacy Statement ***Keysight is an Equal Opportunity Employer.**Required: 5+ years of experience in data engineering, with at least 3 years working with Snowflake. Proven experience with financial data domains including GL, AR, AP, P&L, balance sheet, and forecasting. Strong SQL skills and hands-on experience with dbt, Matillion, or other ELT tools. Integration experience with ERP systems (Oracle, SAP, NetSuite) and other financial tools. Solid understanding of data modeling, cost controls, and platform performance optimization. Preferred: Snowflake SnowPro Certification. Familiarity with SOX, GAAP, or audit-related data requirements. Experience supporting FP&A, Treasury, or Controllership teams. Knowledge of financial hierarchy management, time-series modeling, and period-based aggregation logic. 1. Snowflake Platform & Pipeline Ownership Design and build robust ELT pipelines in Snowflake to integrate financial data from ERP systems (e.g., Oracle, SAP), billing platforms, and planning tools. Deliver clean, well-modeled financial data marts for P&L analysis, cash flow, variance analysis, forecasting, and budget tracking. Optimize Snowflake usage with efficient schema design, warehouse tuning, and compute/storage cost management. 2. Functional Partnership with Finance Teams Collaborate with Finance, FP&A, and Accounting stakeholders to understand business processes, reporting requirements, and data dependencies. Support financial reporting cycles (monthly close, audits, forecast submissions) by ensuring timely, reliable data pipelines. Translate complex financial logic such as allocations, consolidations, and time-based adjustments into scalable data transformations. 3. Data Governance, Quality & Controls Implement role-based access control, secure data zones, and masking policies to manage sensitive financial and employee data. Partner with Data Governance teams to maintain data dictionaries, financial definitions, lineage documentation, and audit trails. Apply rigorous data quality checks to ensure the integrity of financial metrics used in dashboards, planning models, and reports. 4. Technical Leadership & Best Practices Lead the adoption of modern data engineering frameworks using tools like dbt, Matillion, and CI/CD pipelines for Snowflake. Mentor junior engineers and analysts on SQL optimization, data modeling for finance, and best practices for code reuse and maintainability. Drive continuous improvement in pipeline reliability, monitoring, and performance tuning. 5. Integration Across Finance Tech Stack Integrate Snowflake with FP&A tools (e.g., Onestream) and BI/reporting platforms (e.g., Tableau, Power BI, Microstrategy). Build reusable financial data products that serve multiple use cases planning, tax, audit, compliance, and executive dashboards.