VP, Enterprise Data Engineering Manager

This position will be located
onsite
at our HQ in San Diego, CA. Remote or Hybrid is not available for this role.

The
Vice President of Data Engineering
will be responsible for managing various key data implementations across the organization and providing people and technology leadership. The First Vice President will perform data architecture analysis, design, development and testing to deliver data applications, services, interfaces, ETL processes, reporting and other workflow and management initiatives. This role requires a highly motivated individual with strong leadership capability, technical ability, data capability, excellent communication, and collaboration skills including the ability to develop and troubleshoot a diverse range of problems.

Target Range:

$140,000.00 /Yr. - $165,000.00 /Yr.

Actual starting pay will vary based on factors including, but not limited to, geographic location, experience, skills, specialty, and education.

Eligible for an Annual Discretionary Cash Bonus Target: 10%

Eligible for an Annual Discretionary Restricted Stock Units Bonus Target: 10%

Responsibilities:

• Head the development and delivery of enterprise scale mission critical data platforms, i.e. Databricks Lakehouse, GCP services, to meet critical business priorities
• Establish the roadmap and vision for enterprise scale data engineering, executes on this roadmap to deliver shared frameworks for the broader enterprise application development teams
• Build technical excellence by defining and implementing robust data engineering standards and quality frameworks that govern data pipeline development, testing, and deployment across the data platform
• Establish, enforce, and champion modern DataOps and CI/CD practices within the team. Lead the automation of deployment, testing, and monitoring to accelerate delivery speed and ensure data quality
• Provides technical leadership and hands-on guidance to the Data Engineering team to ensure timely and high-quality project delivery and enhancements Mentor engineers in advanced PySpark, SQL, dbt, Fivetran and cloud-native development to maximize team output
• Collaborates with multiple teams, understands the overall enterprise Data Architecture, and develops the end-to-end solutions for data sourcing, data processing/integration, data provisioning and delivery
• Delivers projects to successful completion as defined by predetermined project success criteria including those established by the business, ensuring that projects are delivered on time and within budget
• Focus on designing and developing highly scalable, efficient, and reliable data infrastructure to scale and compute to meet business objectives
• Lead, coach, and develop team, while creating a vision for team and educating cross-functional teams on how to leverage data to identify opportunities to increase revenue and performance
• Drives IT solutions to ensure they meet business needs balanced with a pragmatic and integrated approach to the design of technical solutions
• Remains up to date on key technology, business, and industry trends
• Performs other duties and responsibilities as assigned

Requirements:

• Bachelor's degree in computer science, MIS or related degree
• 10+ years' experience managing Data Engineering and leading Technology Teams
• 7+ years' working with SQL Server and other DB management systems with Cloud and on-PREM data ecosystems
• 7+ years' working with cloud-native data ecosystems (GCP, Azure, AWS) with deep experience in Cloud Data Warehouses (e.g., BigQuery, Snowflake, Databricks), exposure to various database types (SQL and NoSQL) and on-prem databases including SQL Server
• Expertise in Databricks and the Spark ecosystem, including designing and optimizing pipelines using PySpark, implementing the moder data architecture and strong hands-on experience
• Advanced level experience with Python and PySpark (for data processing), advanced SQL, and modern ELT/ETL tools (e.g., Fivetran and dbt).Strong experience with a breadth of Data Integration tools, Databases, Big Data Platforms, Cloud based data platforms and Data Streaming technologies
• Experience leading technical teams (e.g., Data Engineers, Tech Leads), including mentoring, project oversight, and setting technical direction
• Strong experience with breadth of Data Integration tools, Databases, Big Data Platforms, Cloud based data platforms and Data Streaming technologies
• Expertise within Data Architecture and most importantly deep understanding of the overall Data in an enterprise and ability to understand Data in the context of Business goals
• Proficient in building from the ground up a modern next generation Lakehouse platform
• Experience in enterprise implementation, leadership experience, strategic planning, strong business acumen

Preferred:

• Financial Services experience