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.