Senior Data Engineer in Analytics
South San Francisco
Simbe Robotics
Top retailers improve store performance and labor efficiency with our AI & robotics suite, proven to give market-leading product availability & price integrity.
The Senior Data Engineer in Analytics will own the design, implementation, and scaling of our analytics infrastructure to form the foundation of a cohesive analytics ecosystem. This role also empowers data analysts 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. The ideal candidate will have demonstrable experience implementing data warehouses, a strong foundation in SQL and Python, and a mindset for cloud systems design.
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.Apply for this job
Responsibilities
- Data Warehousing: Ingest data from Postgres, Google Cloud Storage, Salesforce, 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 in BI tools. Implement reverse-etl to make aggregate data available in the application database for web application and mobile application use.
- 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.
- Evaluate New Tools and Integrations: Help evaluate and choose the best cloud tools to meet ever-evolving business needs.
- Optimizing and Monitoring Cloud Costs: Monitor and implement controls to ensure data warehousing costs arepredictable and within reasonable levels. Unlock synergies between the application database and data warehouse to reduce overall cloud costs.
- 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
Qualifications
- Technical Qualifications: A bachelor’s or master’s degree in Computer Science (or a related field) is highly recommended but not required. The role requires at least three years of experience with SQL, BigQuery, and GCP. Hands-on expertise with dbt is highly preferred, as is experience interfacing with Postgres. Familiarity with ingesting data via APIs from external software platforms and transforming non-tabular data using Python is a plus. Experience with data streaming is also nice to have.
- Experience & Abilities: Experience implementing and taking full ownership for data warehouses is essential, alongside a proven track record of data modeling for analytical use cases. The ideal candidate will have a background in empowering peers through DataOps best practices, with a strong emphasis on data security and governance. Additionally, a deep understanding of the strengths and weaknesses of both transactional and analytical databases is critical for success in this role.
- Soft Skills: Candidates should have excellent communication skills to effectively convey complex technical concepts across cross-functional teams. An ideal candidate is autonomous and independent, exhibiting a strong sense of ownership and accountability. Additionally, they must be able to evangelize and champion best practices across the organization, ensuring alignment and consistent adoption of best practices.
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.Apply for this job
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
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Tags: Agile APIs BigQuery Computer Science Data management DataOps Data quality Data warehouse Data Warehousing dbt ETL GCP Google Cloud Jira PostgreSQL Python R Robotics Salesforce Security SQL Streaming Testing
Region:
North America
Country:
United States
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