Senior Data Engineer

About the role

You will build and maintain the core enterprise data infrastructure, models, and pipelines to serve as the single source of truth for the company. This role involves partnering with Finance, Sales, Marketing, Product, and HR to ensure data accuracy and accessibility for informed decision-making. You will define the architectural foundations that allow cross-functional teams to trust and explore data independently. The position requires a strong partnership mindset to translate business questions into robust data structures and logic. You will be responsible for ensuring that data pipelines are reliable, performant, and secure at scale. This role will mentor other team members by providing technical guidance and fostering data literacy across the organization. You will play a key role in establishing governance standards that ensure consistency and compliance for all data assets. The work you do will directly influence strategic decisions that impact the entire company.

Key facts

What you'll do

• Develop and maintain scalable warehouse infrastructure for high-quality reporting across the organization.
• Create automated data pipelines connecting databases, APIs, business systems, and data lakes to ensure seamless data flow.
• Build bronze, silver, and gold data models while enforcing governance standards to guarantee data quality and consistency.
• Define data requirements and quality benchmarks in collaboration with internal stakeholders to align analytics with business goals.
• Manage projects from design to production using Github PRs and Jira to maintain clear documentation and version control.
• Implement security and compliance strategies for all data assets to meet regulatory and internal policy requirements.
• Mentor and provide technical guidance to other team members to elevate the overall skill level of the data organization.
• Optimize query performance and data processing workflows to reduce latency and improve user experience.
• Collaborate with data scientists and analysts to ensure that datasets are structured for advanced analytics and machine learning applications.
• Monitor data pipelines for failures or anomalies and establish alerting mechanisms to ensure timely issue resolution.
• Contribute to the selection and evaluation of new data tools and technologies that can enhance the current platform.
• Ensure that all data products are documented and accessible to stakeholders for transparency and reproducibility.

Requirements

• Bachelor or Master degree in Computer Science or a related technical field.
• Minimum 5 years of professional data engineering experience in a comparable role.
• Advanced proficiency in Python and SQL for writing complex queries and data transformations.
• Experience with cloud warehouses like BigQuery, Snowflake, or Databricks using DBT for modeling and orchestration.
• Experience managing data lakes with Apache Iceberg, Delta Lake, or Apache Hudi to handle structured and unstructured data.
• Proven ability to build automated pipelines using Airflow, Dagster, Fivetran, or Airbyte for reliable data ingestion.
• Willingness to work onsite in San Mateo, CA, five days per week to ensure team collaboration and alignment.
• Strong understanding of data modeling principles, including dimensional modeling and entity relationship design.
• Experience with version control systems, particularly Git, for managing code and configuration changes.
• Ability to write clean, maintainable, and well-documented code that adheres to engineering best practices.
• Familiarity with Linux command line and scripting for automation and troubleshooting tasks.
• Commitment to following security and compliance guidelines related to data privacy and handling.

Nice to have

• Experience with data observability tools like BigEye, Monte Carlo, or Great Expectations to monitor data health.
• Familiarity with vector databases for Generative AI applications to support advanced use cases.
• Experience building Gen AI agents for development workflows or business intelligence support to automate repetitive tasks.

Practical notes

• Annual pay range: $140,000 to $210,000 USD.
• Visa sponsorship is available and the company will assist in the process.
• Benefits include 100% premium coverage for employees on at least one healthcare plan, 80% coverage for family premiums, HSA/FSA options, mental health support, parental leave, fertility benefits, professional development stipends, and daily lunches.
• The engagement is Full-time, onsite 5 days per week, requiring consistent presence in the San Mateo office.
• Candidates must be eligible to work in the United States without requiring work authorization sponsorship beyond what the company can provide.
• The role is part of the Data Platforms and Analytics team, focusing on enterprise-level data strategy and execution.
• Professional development stipends are available for employees seeking to enhance their skills through courses or certifications.
• Daily lunches are provided to encourage team interaction and collaboration in the office environment.
• The successful candidate will be expected to participate in regular team meetings and cross-functional discussions.
• This position requires a proactive approach to problem-solving and a willingness to collaborate with stakeholders at all levels.
• The company maintains a culture of transparency, and data professionals are expected to contribute to data-driven decision making.
• The role involves a significant amount of collaboration with technical and non-technical teams to ensure alignment on priorities.
• The successful candidate will have the opportunity to work on impactful projects that influence the direction of the business.
• The position requires a high level of ownership and accountability for the data infrastructure and its performance.
• The company is committed to building an inclusive environment and encourages diverse perspectives in all areas of the business.