Data Engineer

Samara•Redwood City, CA

4d•$120,000 - $140,000•Hybrid

About The Position

We are seeking a Data Engineer to build and own core datasets, design and maintain datasets that serve as sources of truth for key business reporting and decision making, and ensure datasets are accurate, consistent, and understandable by a broad set of stakeholders. The role involves exploring and understanding source systems such as NetSuite, Salesforce, Autodesk Construction Cloud, Bill.com, and other operational platforms to understand how data is generated and how it maps to business processes. You will design scalable data pipelines, build, maintain, and monitor production data pipelines that meet current analytical needs and scale as data volume and complexity increase. Additionally, you will enable access to high-quality data, helping to democratize access to reliable operational and financial data across Finance, Operations, and go-to-market teams, ensuring data products are well documented and suitable for self-service analytics. You will continuously expand analytical coverage by identifying opportunities for new tables, metrics, and derived datasets that unlock additional insight, evaluating work based on clarity and usefulness to decision-makers. The role also involves establishing data standards and best practices, evolving standards for data modeling, testing, documentation, and ownership.

Requirements

1-3 years experience as a data engineer, building core datasets and supporting business verticals as needed.
Hands-on experience shipping scalable data solutions in the cloud (e.g AWS, Databricks, DBT), across multiple data methodologies (e.g dimensional modeling, data marts, medallion schemas)
Strong SQL and Data Modeling Skills. Advanced SQL proficiency with experience designing analytical data models that support reporting and analytics use cases.
Comfort exploring source systems and tracing data through multiple layers of transformation.
Ability and willingness to learn new systems, tools, and business domains. Comfortable working in environments where requirements and priorities evolve.

Nice To Haves

Experience integrating financial, ERP, CRM, or payment systems such as NetSuite, Salesforce, Bill.com or similar tools.
Comfort in aggregating data from multiple sources, with proficiency in handling APIs, geospatial imagery/aerial photography, unstructured web data, and public governmental records.
Experience supporting feature engineering, forecasting, or AI-adjacent analytics.
Curiosity and willingness to adopt AI tools to work smarter and deliver better results.

Responsibilities

Build and Own Core Datasets. Design and maintain datasets that serve as sources of truth for key business reporting and decision making. Ensure datasets are accurate, consistent, and understandable by a broad set of stakeholders.
Explore and Understand Source Systems. Develop a working understanding of source systems such as NetSuite, Salesforce, Autodesk Construction Cloud, Bill.com, and other operational platforms. Understand how data is generated and how it maps to business processes.
Design Scalable Data Pipelines. Build, maintain, and monitor production data pipelines that meet current analytical needs and scale as data volume and complexity increase.
Enable Access to High Quality Data. Help democratize access to reliable operational and financial data across Finance, Operations, and go-to-market teams. Ensure data products are well documented and suitable for self-service analytics.
Continuously Expand Analytical Coverage. Identify opportunities for new tables, metrics, and derived datasets that unlock additional insight. Evaluate work based on clarity and usefulness to decision-makers.
Establish Data Standards and Best Practices. Evolve standards for data modeling, testing, documentation, and ownership.