Staff/Senior Data Engineer

Simberobotics; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Simbe Robotics seeks a Data Engineer to design and scale our analytics infrastructure, enabling DataOps practices for analytics engineers and data scientists. You will partner with the application database team to optimize cloud ecosystems and share large data sets with clients.

The role requires hands-on expertise in SQL, BigQuery, dbt, and cloud data architectures, with senior or staff leveling to be determined during interviews.

Qualifications

• 5+ years of experience with SQL, BigQuery, Terraform, Apache Beam, Airflow, and GCP.

Responsibilities

• Ingest data from Postgres, Google Cloud Storage, Jira, web analytics platforms, into BigQuery.
• Use dbt to transform raw data into data-marts for AI and BI tools.
• Guide data ingestion from and delivery to clients with scalable, traceable feeds.
• Monitor and control cloud costs to keep data warehousing expenditures predictable.
• Establish data testing framework and governance for quality and documentation.

Skills

SQL

BigQuery

Terraform

Apache Beam

Airflow

GCP

dbt

Event-driven analytics

Education

Bachelor's or master's degree in Computer Science or related field

Tools

Postgres

Google Cloud Storage

Jira

BigQuery

dbt

Job description

San Francisco Bay Area (Hybrid — Burlingame office 2-3x/week required)
Must currently reside locally; this is not a remote-eligible role.

Simbe Robotics is a leading retail robotics company providing in-store intelligence solutions that help retailers optimize operations, improve shelf execution, and deliver valuable data insights. Our autonomous robots and multi-modal data collection systems are transforming how retailers manage inventory and make data-driven decisions.

Position Overview

The Data Engineer in will own the design, implementation, and scaling of our analytics infrastructure to form the foundation of a cohesive analytics ecosystem. This role also empowers analytics engineers and data scientists to follow DataOps best practices to independently create metrics. Additionally, the Data Engineer will interface with the application database team to synergistically improve the overall cloud ecosystem, enabling scalable ways to share large volumes of data with clients. The ideal candidate will have demonstrable experience implementing data warehouses, a strong foundation in SQL and Python, and a mindset for cloud systems design.
Leveling (Senior or Staff) will be determined through the interview process based on your background and technical depth.

Data Warehousing
Ingest data from Postgres, Google Cloud Storage, Jira, web analytics platforms, and other sources into BigQuery. Use Data Build Tool (dbt) to transform raw data into user friendly “data-marts” for use by AI and BI tools.

External Data Exchange
Guide the organization on how data is ingested from and delivered to clients. Establish the infrastructure for scalable and traceable inbound feeds (product catalogs, planograms) and large outbound delivery (reporting extracts, cloud-native data sharing)

Optimizing and Monitoring Cloud Costs
Monitor and implement controls to ensure data warehousing costs are predictable and within reasonable levels. Unlock synergies between the application database and data warehouse to deliver timely insights and reduce overall cloud costs.

Data Quality & Governance
Use dbt to establish a robust data testing framework that ensures data remains accurate and trustworthy, while also producing a comprehensive suite of metric definitions and documentation accessible to anyone in the organization. Champion DataOps best practices across teams to cultivate a consistent, high-quality approach to data management and analytics.

Security & Compliance
Help ensure account permissions remain appropriate and enforced across the data consumption layer. Implement controls to ensure the data warehouse maintains compliance with GDPR, PII laws, SOC 2, and other regulations

Technical Qualifications

• Bachelor's or master's degree in Computer Science or related field highly recommended, not required

• 5+ years of experience with SQL, BigQuery, Terraform, Apache Beam, Airflow, and GCP

• Hands-on expertise with dbt and event-driven analytics highly desirable

Experience & Abilities:

• Proven experience implementing and owning data warehouses end-to-end

• Track record of data modeling for analytical use cases

• Background empowering peers through DataOps best practices

• Strong emphasis on data security and governance

• Deep understanding of the strengths and weaknesses of transactional vs. analytical databases

Soft Skills:

• Excellent communication skills; able to convey complex technical concepts across cross-functional teams

• Autonomous and independent, with strong ownership and accountability

• Able to evangelize and champion best practices, ensuring alignment and consistent adoption across the org

At Simbe, you will be at the forefront of retail innovation, working with cutting‑edge AI and robotics technologies to transform retail operations. Our culture is dynamic, inclusive, and driven by a passion for improving the way retailers operate and serve their customers. Join us to be a part of a team that is not only reshaping the future of retail but also offering immense value to our clients worldwide.

Simbe Values: R. E. T. A. I. L.

Result Driven - We are customer‑centric and results‑driven. We strive to create immense value for our team, partners, customers, and investors.

Empathetic - We are sensitive and mindful. We support each other in challenging times, both professionally and personally.

Transparent - We highly value open communication internally, and with our partners and customers. We are receptive to feedback.

Agile - We are agile and always eager to learn. We quickly adapt to changes and customer needs.

Innovative - We are bold and innovative, with an intense focus on product design and user experience.

Leaders - We strive for excellence. We are accountable, the best at what we do, and leaders in our field.