Sr. Data Engineer

Premier Nutrition Company’s Enterprise Data Intelligence team is building and operating cloud-native data infrastructure that powers analytics, reporting, and data science across a SaaS-based environment. In this role, you will design, develop, and maintain scalable cloud data pipelines and ETL/ELT workflows, while helping strengthen DataOps operational excellence and ensuring the data warehouse is administered, monitored, and optimized end to end. This is a hybrid position based in Emeryville, CA with a focus on reliable production delivery, data quality, and continuous improvement for enterprise data assets. What you’ll do Design, build, and maintain cloud-native data pipelines and infrastructure to support analytics, reporting, and data science use cases in a SaaS-based environment. Own the full data lifecycle, from requirements gathering through design, ingestion, transformation, modeling, testing, deployment, monitoring, and production support. Implement and manage ELT pipelines using Fivetran , dbt , and Python to deliver reliable, scalable data solutions. Develop and maintain data models, data marts, APIs, and automation scripts to streamline analytics workflows. Design and deploy Snowflake database schemas, tables, and views across multiple environments including DEV , QA/UAT , and PROD . Work with stakeholders to translate business requirements into robust technical designs. Provide documentation, training, and enablement to support adoption of enterprise data assets. Protect pipeline reliability by monitoring production schedules, troubleshooting failures, and ensuring smooth execution. Monitor and investigate data quality issues and drive solutions when problems arise. Administer Snowflake security strategy and database management. Fine-tune and optimize databases, queries, and pipelines for performance and efficiency. Identify opportunities for automation to improve Enterprise Data Intelligence team effectiveness and operating efficiency. Research and test new technology solutions, including supporting assessment of architectural or database design changes needed for enterprise adoption. Follow documented procedures for database configuration, maintenance, upgrades, testing, and deployment. Ensure best practices for enterprise database administration to support user experience and sustainable design. What you bring Bachelor’s degree in computer science, Engineering, Information Systems, or a related technical discipline. 5+ years of experience as a Data Engineer in cloud-native and SaaS-based environments, supporting enterprise data platforms built on data warehouses, data lakes, and application databases (including Snowflake , Oracle , or SQL Server ). 7+ years of SQL experience, with proven ability to write, optimize, and maintain complex queries and stored procedures. Programming experience in Python , Scala , or other scripting languages for automation, data transformation, and integration. Hands-on experience building ELT/ETL pipelines and dimensional models/data marts using modern tools such as dbt , Fivetran , or equivalent frameworks. Demonstrated experience with SaaS data sources and APIs, including integrations from ERP (e.g., NetSuite ), CRM, and planning tools (e.g., Oracle EPM , O9 , or Salesforce ). Exposure to or hands-on experience with AI/LLM frameworks such as Snowflake Cortex or MCP to enhance automation and data intelligence. Experience with data integration and orchestration tools such as Dell Boomi , Airflow , Azure Data Factory , or equivalent tools. Strong understanding of data governance, observability, lineage, and data quality management in a cloud environment. Experience with Git -based version control (e.g., GitHub, GitLab) and CI/CD workflows for deployment across DEV, QA, and PROD. Working knowledge of cloud platforms (preferably Azure , with exposure to AWS or GCP ) and secure data exchange mechanisms (APIs, SFTP ). Excellent communication and collaboration skills for cross-functional work in a distributed SaaS organization. Willingness to be on call for night/weekend production support. Ability to think strategically about tools and technologies that enable analytics. Technologies you may work with Fivetran , dbt , Python , Snowflake , SQL , Scala APIs , NetSuite , Oracle EPM , O9 , Salesforce Snowflake Cortex , MCP Dell Boomi , Airflow , Azure Data Factory GitHub , GitLab , CI/CD Azure , AWS , GCP , SFTP Preferred qualifications Master’s degree in Computer Science, Engineering, Information Systems, or a related technical discipline. Hands-on knowledge of at least one key BI tool such as Tableau , SAP BO , Oracle BI , or MS Power BI . Experience working in the CPG industry. Compensation USD 170,000 - 180,000 per year. Benefits Year-round ½ day Fridays . In-office massages. Free lunches & snacks. Dogs in the office. Culture of belonging celebrations. Engaging in-office events such as bring your kids to work day . 6% 401k match after 1 year. Generous paid family leave regardless of gender. All positions are bonus-eligible . Company-wide volunteer days. Company-matched charitable donations. No employee handbook. No dress code. Coaching conversations instead of performance reviews. Walking meetings. The work environment If you are based in the greater Bay Area, you will walk into the Emeryville office each Tuesday morning and begin the in-person portion of the hybrid week at the weekly all-company meeting. Every employee who lives within 100 miles of the offices is expected to come in Tuesday through Thursday. Mindsets the team values Challenger Mindset with bias for action and comfort taking smart risks. Act as a builder by creating for the future. Enterprise strategic view across the full company perspective. Challenge ideas respectfully and share real opinions with conviction. Bring people along by providing context and cascading information openly and inclusively. Interview process A quick 30-minute phone chat with a Talent Acquisition team member. A short series of in-person or video interviews in a 1:1 setting. A case study or job task may be included. An in-depth consultative process to ensure the right person is hired for the right job. Interviewers must arrive with a strong yes or no vote beforehand, with reasons to avoid groupthink. A trained, disinterested bias blocker will be present to help mitigate bias. The hiring manager makes the final decision. #J-18808-Ljbffr