Principal Engineer, Data Modeling

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. 

Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, Bangalore, London, Melbourne, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events (pre and hopefully post-Covid) and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive. Visit us at Netskope Careers. Please follow us on LinkedIn and Twitter@Netskope.

With a mission to evolve security for the way people work, Netskope, a cloud security company, was founded by early architects and distinguished engineers from security and networking leaders like Palo Alto Networks, Juniper Networks, Cisco, and VMware.

 We are looking for an enthusiastic data architect to build unified enterprise data models and establish data standards and processes to scale agile data infrastructure on-prem and in the cloud. The Data team works closely with the product team to build highly scalable systems to tackle real-world data problems. Our customers depend on us to provide accurate, real-time, and fault-tolerant solutions to their ever-growing data needs. The principal position is responsible for leading enterprise data strategy and defining the data analytics' future roadmap.

 Role and Responsibilities:

• Engage with business leaders across all business units to understand business requirement and translate them into scalable technical solutions

• Lead large-scale data lake project and establish master product data with a focus on data consistency and quality

• Establish data standards and processes to improve data usability, availability, and reliability 

• Build data quality framework to measure and monitor data quality 

• Own enterprise-level unified data models and maintain data dictionary

• Mentor junior and intermediate level developers, data engineers on data architecture best practices

Qualifications:

• Extensive hands-on experience in designing data models, data profiling, ELT & ETL processes, and BI development

• Advanced SQL, python, and scripting skills and experience in visualization tools such as Google Looker, Tableau, or Microsoft Power BI

• Expert knowledge of data modeling and understanding of different data stores (ex. NoSQL, Relational, Columnar) and their benefits and limitations under particular use cases

• Proficiency in SQL, HiveQL, SparkSQL, and Python. Knowledge of Java, Scala, and distributed technologies such as Spark, Kubernetes is a plus

• Experience in driving large-scale enterprise data lake projects in the cloud and building data quality framework

• Experience with data privacy and data security aspects are highly desirable

• Domain expertise around data architecture, data governance, and system design integrations