Senior Analytics Engineer

General Purpose:

We are seeking a talented and proactive Analytics Engineer to join our growing Business Intelligence team. In this pivotal role, you will bridge the gap between raw data and actionable insights, applying software engineering best practices to data modeling, transformation, and governance. You will empower business users and analysts by building clean, reliable, and well-documented data assets, ensuring our stakeholders have trusted data at their fingertips to drive critical business outcomes in the dynamic CPG landscape.

Duties and Responsibilities:

Data Modeling & Transformation (dbt & Databricks):

• Design, develop, and maintain scalable, efficient, and well-documented data models using dbt (data build tool) in our Databricks Lakehouse.

• Transform raw data from various source systems (e.g., ERP, CRM, marketing platforms, supply chain) into clean, curated, and optimized datasets (Bronze, Silver, Gold layers) for analysis and reporting.

• Implement data quality tests and monitoring within dbt to ensure data accuracy, completeness, and consistency.

• Optimize SQL queries and dbt models for performance on Databricks' Spark engine.

Data Platform Development & Governance (Databricks & Terraform):

• Collaborate with Data Engineering to understand data ingestion patterns and contribute to the evolution of our Databricks Lakehouse architecture.

• Utilize Databricks features such as Unity Catalog, SQL Endpoints (Warehouses), and Cluster Policies to build a secure and governed data environment.

• Manage and automate the provisioning and configuration of Databricks resources and security settings (e.g., users, groups, service principals, grants) using Terraform.

• Support the implementation of data governance policies, including data lineage, metadata management, and access controls within Unity Catalog.

BI Tool Enablement & Support (Sigma & Tableau):

• Work closely with business analysts and stakeholders to understand their analytical needs and translate them into robust data models.

• Enable self-service analytics by building intuitive and performant datasets directly consumable by Sigma and Tableau users.

• Provide technical support and guidance to BI analysts on best practices for data consumption, visualization, and dashboard development in Sigma and Tableau.

• Support and optimize Sigma write-back capabilities, ensuring governed and efficient data contribution from business users back into Databricks.

Collaboration & Best Practices:

• Champion software engineering best practices for analytics code, including version control (Git), modularity, testing, and continuous integration/continuous delivery (CI/CD) principles.

• Contribute to defining and maintaining our team's data modeling standards, documentation guidelines, and overall data development lifecycle.

• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

• Performs other duties as assigned.

People Manager: No

Education:

• Bachelor's Degree required

• Master's Degree preferred

• Tableau, AWS, Databricks certification preferred

Required Knowledge, Skills, Abilities, & Other Characteristics

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field. (Master's degree preferred)

• 5+ years of experience in an Analytics Engineering, Data Analyst, or Data Engineer role with a strong focus on data modeling and transformation.

• Expert proficiency in SQL with a deep understanding of dimensional modeling (Kimball), data warehousing concepts, and query optimization.

• Hands-on experience with dbt (data build tool) for managing complex data transformations and building robust data models.

• Strong experience with Databricks, including Spark SQL, Delta Lake, Databricks SQL Endpoints (Warehouses), and Unity Catalog.

• Familiarity with Infrastructure as Code (IaC) principles and Terraform for managing cloud resources and platform configurations, particularly related to Databricks security and environment setup.

• Proficiency in at least one modern BI tool, with strong preference for Sigma and/or Tableau, including experience building data sources, reports, and dashboards. Experience with Sigma's write-back capabilities is a significant plus.

• Experience with version control systems (Git) and collaborative development workflows.

• Ability to work effectively in a fast-paced, agile environment, managing multiple priorities and projects.

• Excellent communication, interpersonal, and problem-solving skills, with a passion for collaborating with diverse teams.

Preferred Knowledge, Skills, Abilities, & Other Characteristics

• Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.

• Experience with Sigma's write-back capabilities is a significant plus.

• Experience with cloud platforms such as AWS (preferred), Azure, or GCP.

• Exposure to data ingestion tools like Airbyte (preferred), Fivetran, or Workato.

• Basic scripting skills in Python for data manipulation, automation, or API interactions (GraphQL is a plus).

• Experience in the CPG (Consumer Packaged Goods) industry.

• Understanding of data governance, data quality, and metadata management principles.

Work environment: Office environment

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