Data Engineer

Premier Nutrition•Emeryville, CA

35d•Hybrid

About The Position

As a Data Engineer, you will help our company solve their most challenging problems and drive decisions with data. As a member in our Enterprise Data Intelligence team, you will be at the center of data and analytical innovation and adoption. In this role, you will drive value by migrating, acquiring, maintaining, and evolving our data integration process and platform. Activities range from data acquisition and validation, designing and implementing ETL/ELT data pipelines, designing and implementing databases, job suite execution and monitoring, support testing, troubleshooting, and system analysis. You will be collaborating with all our departments to build end-to-end data infrastructure and pipelines that promote reporting and advanced analytics and further business process evaluation.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related technical disciplines.
5+ years of experience as a Data Engineer working within cloud-native and SaaS-based environments, supporting enterprise data platforms built on data warehouses, data lakes, and application databases (e.g., Snowflake, Oracle, SQL Server).
5+ 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 designing, building, and maintaining ELT/ETL data pipelines, dimensional models, and data marts using modern tools such as dbt, Fivetran, or equivalent cloud-based frameworks.
Demonstrated experience working with SaaS data sources and APIs, integrating data from cloud-based systems such as 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 (e.g., Snowflake Cortex, MCP, or similar technologies) to enhance automation and data intelligence.
Experience with data integration and orchestration tools (e.g., Dell Boomi, Airflow, Azure Data Factory, or equivalent).
Strong understanding of data governance, observability, lineage, and data quality management in a cloud environment.
Experience using Git-based version control systems (e.g., GitHub, GitLab) and CI/CD workflows for deployment across multi-environment pipelines (DEV, QA, 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, with the ability to work cross-functionally in a distributed SaaS organization.
Problem-Solving: Ability to analyze complex data challenges and develop innovative solutions that align with business objectives.
Get Things Done: Great work ethic and moves with a sense of urgency.
Drives Continuous Improvement: Always focusing on effective and efficient work and ways to get better.
Obsesses over the Details and committed to paying attention to the details
Demonstrated excellent verbal/written communication skills.
Life long learner: A passion for staying up-to-date with the latest trends and advancements in data engineering and related technologies.
Provocative thinker who is courageous to share his or her thoughts regardless of the level of the audience
Self-motivated individual who can identify issues/opportunities for improvement and be proactive in addressing them
Able to wear many hats and multitask as priorities evolve and change
Demonstrates ownership of outcomes vs being an order taker of tasks
Manage the forward progress on multiple projects and determine priority order
Bring a sense of fun, passion and positive attitude to every day

Nice To Haves

Master’s degree in Computer Science, Engineering, Information Systems, or related technical disciplines preferred.
Hands on knowledge with at least one key BI market tool (Tableau, SAP BO, Oracle BI, MS Power BI) is a plus.
Must be willing to be on call for night/weekend production support.
Ability to think strategically about tools and technologies that enable analytics.
Experience working in CPG industry.

Responsibilities

Design, build, and maintain cloud-native data pipelines and infrastructure to support analytics, reporting, and data science use cases in a SaaS-based environment.
Perform all stages of the data lifecycle: requirements gathering, design, ingestion, transformation, modeling, testing, deployment, monitoring, and production support.
Implement and manage ELT pipelines using tools such as Fivetran, dbt, and Python, delivering reliable and scalable data solutions.
Develop and maintain data models, data marts, APIs, and automation scripts to streamline analytics workflows.
Design and deploy database schemas, tables, and views in Snowflake across multiple environments (DEV, QA/UAT, PROD).
Collaborate with stakeholders to translate business requirements into robust technical designs.
Support documentation, training, and enablement to drive adoption of enterprise data assets.
Protect the data pipeline! Your mission is to monitor the production schedule, troubleshoot any failures, and ensure that the processes are running smoothly.
Monitor data quality and dig in deep to find solutions to problems when they arise.
Administer Snowflake security strategy and database management.
Fine-tune and optimize databases, queries, and pipelines for improved performance and efficiency.
Proactively identify processes that would benefit from system automation to improve the Enterprise Data Intelligence team effectiveness and increase operating efficiencies.
Research and test new technology solutions, assist in vetting architectural changes/database design that would have to occur to support enterprise adoption and determine impacts.
Follow documented procedures for configuring, maintaining, upgrading, testing, and deploying as a database administrator. Ensure best technical practices are followed for all enterprise database administration for the best user experience and sustainable design.