Senior Data Engineer

IN-KA-Bangalore

Global Careers (External)

Req #: 48289
Type: Regular
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Keysight Technologies Inc.

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				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 Senior Data Engineer with strong expertise in Snowflake and functional knowledge of Sales and Services data domains to help us build scalable, trusted data products that enable sales optimization, customer success, and services transformation. You'll lead the design and development of high-performance data pipelines supporting critical use cases like sales forecasting, renewals, churn prediction, cross-sell/upsell insights, and field service analytics.

Responsibilities:
1. Snowflake Platform & Pipeline Development
* Lead the architecture and development of robust, scalable ELT pipelines in Snowflake to integrate data across Sales (e.g., Salesforce), Services, Customer, and Financial systems.

* Build data models and marts to support customer 360 views, sales pipeline tracking, renewal performance, and service operations metrics.

* Partner with analytics teams to ensure data structures support predictive modeling, segmentation, and opportunity scoring.

2. Functional Understanding & Business Partnership
* Work closely with Sales Ops, Service Ops, and Customer Success teams to translate business needs into scalable Snowflake-based data solutions.

* Understand key sales metrics (e.g., bookings, pipeline, win rate, renewal rate) and service KPIs (e.g., resolution time, service attach rate) to drive relevant data designs.

* Lead workshops with functional stakeholders to gather requirements, prioritize data assets, and define SLA-based deliverables.

3. Data Modeling & Performance Optimization
* Design performant and reusable data models tailored for sales forecasting, churn risk analysis, and services coverage optimization.

* Tune Snowflake compute and storage performance using Warehouse scaling, Resource Monitors, and Query Profiles.

* Apply cost governance practices to monitor and optimize platform efficiency.

4. Governance, Quality & Security
* Implement and manage RBAC, secure views, and data masking policies to ensure only authorized access to sensitive sales/customer/service data.

* Work with governance teams to maintain trusted data dictionaries, lineage, and quality rules across domains like lead-to-cash, case management, and customer entitlements.

* Support compliance with privacy regulations (e.g., GDPR) across customer and engagement data.

Qualifications:

Careers Privacy Statement 

***Keysight is an Equal Opportunity Employer.***

Required:
* 5+ years of experience in data engineering, with 3+ years focused on Snowflake development and architecture.

* Strong understanding of Sales and Services business processes, KPIs, and data flows (e.g., CRM, CPQ, renewals, service cases).

* Proficiency in SQL, Python, and modern ELT tools such as Matillion, dbt, or Fivetran.

* Proven experience integrating Snowflake with Salesforce, ERP, and service ticketing systems.

* Hands-on experience with data modeling, data quality frameworks, and cloud-based pipeline orchestration.

Preferred:
* Snowflake SnowPro Certification.

* Experience working in Agile/Scrum teams supporting Sales Operations, Customer Success, or Field Service functions.

* Familiarity with BI/analytics tools like Tableau or Power BI and their integration with Snowflake.

* Exposure to predictive use cases like churn modeling, account scoring, and customer segmentation.
			
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