About The Position

The Senior Data Analytics Engineer is considered a leading role in shaping the analytics platform, data modeling practices, and decision-enabling systems at isolved. As a senior individual contributor, you will act as a technical and strategic thought partner across the business-working with data engineers, analysts, product teams, and AI stakeholders to turn raw data into reliable, governed, and insightful data assets. This is a hands-on, high-impact role that requires deep expertise in data modeling, dbt, cloud-based data stacks, and AI-ready data foundations, along with a strong product mindset and ability to partner closely with stakeholders to drive business value.

Requirements

  • 7+ years of experience in analytics engineering, data engineering, or data analytics roles.
  • Expert in dbt and modern data transformation pipelines (dbt Cloud or Core)
  • Deep understanding of data modeling techniques (dimensional modeling, star/snowflake schema, slowly changing dimensions, data vault, etc.)
  • Proficient in SQL (performance tuning, complex joins, CTEs, window functions)
  • Strong working knowledge of cloud data warehouses (e.g., Databricks preferred, Snowflake, BigQuery, Snowflake, etc)
  • Comfortable with Git-based workflows, CI/CD, and software engineering best practices in analytics contexts
  • Experience collaborating with cross-functional teams and translating ambiguous business needs into structured data models
  • Demonstrated experience owning data domains and metrics at scale
  • Strong communication and storytelling skills; able to explain complex data topics to both technical and non-technical audiences
  • Proficient in Python, with the ability to automate data workflows and support AI-enabled analytics use cases as needed

Nice To Haves

  • Experience with modern BI tools (PowerBI, Looker, Mode, Hex, Tableau, etc.)
  • Some exposure to Spark
  • Background in experimentation (e.g., A/B testing infrastructure and analysis)

Responsibilities

  • Lead the design and evolution of our semantic layer and analytics data models using dbt and modern warehouse platforms, including structures that support AI-assisted analysis and reusable data products.
  • Define and enforce best practices in data transformation, versioning, testing, documentation, and automation of repetitive data quality checks.
  • Collaborate closely with analysts, product managers, and data engineers to align modeling work with business use cases.
  • Own the lifecycle of metrics and definitions, ensuring consistency, trust, and reusability across the organization.
  • Drive the implementation of self-service data capabilities, empowering teams through curated datasets, intuitive tooling, and AI-assisted discovery where appropriate.
  • Provide technical mentorship and guidance to analytics engineers and analysts across teams.
  • Act as a bridge between analytics and engineering, translating requirements into scalable and performant data infrastructure.
  • Contribute to governance initiatives (e.g., data cataloging, lineage, quality monitoring, and standards for approved AI tool usage) to increase trust in data products.
  • Optimize and tune warehouse performance for cost and scale (Databricks preferred, BigQuery, Snowflake, etc), including identifying opportunities to automate recurring optimization and monitoring tasks.

Benefits

  • isolved People Cloud™ is a connected HCM platform with built-in artificial intelligence (AI) and analytics that brings together HR, payroll, benefits, workforce management and talent management in one experience.
  • Visit www.isolvedeebenefits.com for a comprehensive list of our employee total rewards offerings.
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