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Principal Data Engineer
Make Next Happen Now. For over 30 years, Silicon Valley Bank (SVB) has helped innovative companies and their investors move bold ideas forward, fast. SVB provides targeted banking services to companies of all sizes in innovation centers around the world. In fact, a majority of the most compelling Fintech disruptors bank with us. Our clients include: Beyond Meat, Shopify, HelloFresh, Cloudera, and Andreessen Horowitz, just to name a few. We help our clients grow, too. More than half of the innovation companiesthat completed an IPO in the last two years are our clients.
This is a unique career opportunity is for a highly experienced Data Engineer with broad based data skills in designing & building data warehouses, data lakes and real-time and batch data integrations. The successful candidate should have hands-on implementation experience in Big Data technologies, event processing frameworks and ETL tools.
The Data Engineering team at Silicon Valley Bank is responsible for delivering data solutions that support all lines of business across the organization. This includes providing data integration services for all batch data movement; managing and enhancing the data warehouse, Data lake and dependent data marts; providing support for analytics and business intelligence consumers.
About the Role:
As Principal Data Engineer you will be responsible for building the data platform that support data integrations: building data pipelines to share enterprise data, designing and building an AWS data lake with appropriate data access, data security, data privacy and data governance. Use agile engineering practices and various data development technologies to rapidly develop creative and efficient data products and data pipelines.
Work closely with the Data Architects, Solution Architects & Data Modelers to enhance the Data products, constantly identify a backlog of tech debts in line with identified upgrades and provide technical solutions & implement the same. Identify inefficiencies, optimize processes and data flows, and make recommendations for improvements.
A strong candidate will use operational skills to drive efficiency and speed, have expertise in building repeatable data engineering processes, use strong agile and project management skills to deliver data products.
Manage deliverables of developers, perform design reviews and coordinate release management activities.
7+ years of experience in designing & building Data Warehouse and Business Intelligence dashboards - Extensive knowledge of data warehouse principles, design, and concepts.
5+ years of experience in creating and maintaining ETL processes and architecting complex data pipelines - knowledge of data modeling techniques and high-volume ETL/ELT design.
1+ years of experience with public cloud-based data platforms especially building Data Lake on the cloud, Data Warehousing constructs like Redshift, Snowflake and machine learning capabilities such as Sagemaker, DataRobot
1+ years of experience in designing data privacy related constructs to enable data tokenization, encryption & data access controls on a public cloud data lake
1+ years of experience in Data Engineering related AWS services like Lake formation, Glue, S3, Lambda, DynamoDB and other AWS accelerators
Knowledge of data modeling techniques and high-volume ETL/ELT design.
SQL - development experience in at least one scripting language (Python etc.), adept in tracing and resolving data integrity issues
Use agile engineering practices and various data development technologies to rapidly develop creative and efficient data products
Identify inefficiencies, optimize processes and data flows, and make recommendations for improvements
Communicate with other developers across teams, both for ad hoc problem solving, and check-ins/discussions with other initiatives
Support non-technical team members in understanding the technical implications of design decisions
Perform code reviews and aid in performing technical platform audits
AWS Services like S3, Glue, Lambda, DynamoDB, Redshift, Lake formation, Sagemaker, Quicksight, Athena
Scripting and languages: Python, SQL
ETL tools like Informatica
Knowledge of Data Modeling, Data protection/compliance standards like GDPR, CCPA, HIPAA
© 2021 SVB Financial Group. All rights reserved. SVB, SVB FINANCIAL GROUP, SILICON VALLEY BANK, MAKE NEXT HAPPEN NOW and the chevron device are trademarks of SVB Financial Group, used under license. Silicon Valley Bank is a member of the FDIC and the Federal Reserve System. Silicon Valley Bank is the California bank subsidiary of SVB Financial Group (Nasdaq: SIVB ).
Equal Employment Opportunity
Silicon Valley Bank is an equal opportunity employer and is dedicated to expanding its commitments and investments to create a more diverse, equitable and inclusive company culture and innovation ecosystem. We are strongly committed to the values and policy of equal employment opportunity across our employment practices.
Silicon Valley Bank is registered in England and Wales at Alphabeta, 14-18 Finsbury Square, London EC2A 1BR, UK under No. FC029579. Silicon Valley Bank is authorised and regulated by the California Department of Business Oversight and the United States Federal Reserve Bank; authorised by the Prudential Regulation Authority with number 577295; and subject to regulation by the Financial Conduct Authority and limited regulation by the Prudential Regulation Authority. Details about the extent of our regulation by the Prudential Regulation Authority are available from us on request.