Principal Data Engineer

Company Description

Zscaler (NASDAQ: ZS) accelerates digital transformation so that customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange is the company’s cloud-native platform that protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. 

With more than 10 years of experience developing, operating, and scaling the cloud, Zscaler serves thousands of enterprise customers around the world, including 450 of the Forbes Global 2000 organizations. In addition to protecting customers from damaging threats, such as ransomware and data exfiltration, it helps them slash costs, reduce complexity, and improve the user experience by eliminating stacks of latency-creating gateway appliances. 

Zscaler was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. Zscaler’s purpose-built security platform puts a company’s defenses and controls where the connections occur—the internet—so that every connection is fast and secure, no matter how or where users connect or where their applications and workloads reside

Job Description

Position:  Principal Data Engineer
Location: Remote within United States

About the team: As part of the IT group, we are responsible for executing our enterprise data strategy which emphasizes data management maturity, fosters a robust data culture, and architects a best-in-class enterprise data platform.  We have the ultimate goal to provide trusted data and insights at scale which enable corporate and functional data-driven decision making. We are fueled by organic innovation, internal collaboration and adoption of data visualization, data management, reporting automation, AI/ML and integration tools. We leverage best practices and alignment through our Enterprise Data Community to deliver speed to insight, scale, control and enablement. The team is distributed across the United States and India and is composed of data engineers, data analysts, visualization developers, and infrastructure specialists. 

Must-Have Experience

• Advanced SQL & python (API integration)
• Knowledge on data integration tools & building modern data stack
• Data model design for enterprise level data applications
• Attitude to continuously explore, learn, & find ways to add value

Responsibilities/What You’ll Do:

• Architect, design, and build large-scale data operations at Zscaler with a focus on scalability, latency, efficiency, standardization, interoperability and fault-tolerance
• Work closely with senior leadership, business analysts, & engineering team to strategize and implement data initiatives
• Drive technical architecture to accelerate solutions designs. Explore, learn, & recommend new tools & technologies that help the data platform to stay up to date and operate in an efficient way.
• Improve, and implement data engineering & analytics engineering best practices
• Lead a team of data Engineers and own the data integration components of data warehouse application
• Hands on in designing & developing key initiative data pipelines to integrate various applications using supported APIs & model the data in cloud data warehouse to support the reporting requirements
• Perform code reviews, manage code performance improvements and teach standards for code maintainability
• Collaborate with Data Engineering, Analytic engineering & BI teams to define and implement scalable data models & security requirements.
• Solve technical problems of the highest scope and complexity
• Propose ideas to improve the scale, performance, and capabilities of the Data Platform

Qualifications

Qualifications/Your Background:

• 12+ years of experience in data warehouse design & development
• Proficiency in building data pipelines to integrate business applications (salesforce, Netsuite, Google Analytics etc) with Snowflake
• Extensive experience in generating architecture recommendations with the ability to implement them
• Strong hands-on experience in modern data stack tools like Keboola, Matillion,Airbyte, IICS, DBT
• Must have proficiency in SQL and data modeling techniques (Dimensional) – able to write structured and efficient queries on large data sets
• Must have hands-on experience in Python to extract data from APIs, build data pipelines.         
• Solid understanding of advanced snowflake concepts like Streams, tasks, warehouse optimizations, SQL tuning/pruning
• Must have the knowledge of data visualization tools such as Tableau, and/or Power BI
• Familiarity with data mesh style a