Senior Data Engineer
About The Position
As a member of our Data Platforms and Analytics Team and reporting directly to the Head of Data, you will be responsible for developing the core enterprise data warehouse infrastructure, data models, and pipelines at Verkada. We aim to provide a single reporting source of truth for enterprise data with clear business data definitions to empower internal Finance, Sales, Marketing, Product and HR teams to make informed data driven decisions. Our strategy emphasizes automation, scalable architecture, and accuracy, while providing iterative improvements over time. We are committed to a thriving in-office culture. This role requires you to be onsite at our HQ in San Mateo, CA.
Requirements
- Bachelor's or Master's degree in Computer Science or a related technical field.
- Minimum of 5 years of professional data engineering experience.
- Advanced skill in Python and SQL.
- Expertise with cloud warehouses such as BigQuery, Snowflake, or Databricks leveraging DBT as a data modeling framework.
- Expertise in managing data lakes with open source file formats such as Apache Iceberg, Delta Lake or Apache Hudi
- Proven track record in constructing automated pipelines using Airflow, Dagster, Fivetran, and / or Airbyte from various operational databases, API endpoints, business systems, and data lakes.
- Expert-level proficiency in SQL and Python is required.
- Must be willing and able to work onsite five days per week.
Nice To Haves
- Experience building / managing data observability and data quality platforms such as BigEye, Monte Carlo and Great Expectations is a plus
- Familiarity or experience building vector databases for Generative AI use cases is a plus.
- Experience building Gen AI agents to optimize development workflows within data engineering is a plus.
- Experience building Gen AI agents for providing support for business intelligence related inquiries is a plus
Responsibilities
- Engineer and maintain efficient, scalable warehouse infrastructure that facilitates high-quality, accurate insights and reporting.
- Design, implement and manage automated data pipelines from various data sources including databases, API endpoints, business systems, and data lakes.
- Collaborate across departments to develop bronze, silver, and gold data models, enforcing business alignment and data governance.
- Partner with Finance, Sales, Marketing, Product, and HR stakeholders to define data pipeline sources, data modeling requirements, and data quality standards.
- Oversee the entire project lifecycle, moving initiatives from initial design through to production leveraging development standards such as Github PR reviews and Jira sprint board management.
- Create and deploy strategies to maintain data security, integrity, and regulatory compliance.
- Provide leadership and guidance to grow and mentor future members of the data engineering team.
Benefits
- Healthcare programs that can be tailored to meet the personal health and financial well-being needs - Premiums are 100% covered for the employee under at least one plan and 80% for family premiums under all plans
- Nationwide medical, vision and dental coverage
- Health Saving Account (HSA) with annual employer contributions and Flexible Spending Account (FSA) with tax saving options
- Expanded mental health support
- Paid parental leave policy & fertility benefits
- Time off to relax and recharge through our paid holidays, firmwide extended holidays, flexible PTO and personal sick time
- Professional development stipend
- Wellness/fitness benefits
- Healthy lunches provided daily
- Commuter benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
