If you are a strategic thinker passionate about driving solutions in analytics, you have found the right team.

As an Analytics Solutions Manager- Associate within our analytics organization, you lead development of dimensional and domain-oriented analytics data models optimized for BI and self-service consumption. You will translate stakeholder needs into governed datasets and KPI definitions in Snowflake and/or Databricks using SQL as the primary transformation language. You will embed data quality, documentation, and performance best practices so downstream teams can reliably reuse models for self-service reporting.

Job Responsibilities

Lead development of dimensional and/or domain-oriented analytics data models optimized for BI and self-service consumption.
Design and maintain a semantic layer defining standardized metrics, dimensions, entities, and business definitions.
Translate stakeholder requirements into clear modeling deliverables, including grains, entities, metric logic, and acceptance criteria.
Build transformations primarily in SQL and leverage Python for complex logic, automation, and validation as needed.
Implement data quality controls, including tests, reconciliations, and anomaly checks tied to business-critical metrics.
Optimize model performance in Snowflake and/or Databricks by applying efficient joins and storage/performance strategies.
Collaborate with upstream teams to align source-to-model meaning, including semi-structured and NoSQL data considerations.
Establish modeling standards covering naming conventions, documentation, lineage, metric governance, and change management.
Document curated datasets and produce user guidance to enable correct adoption of semantic definitions.
Support consumers by troubleshooting metric questions and improving usability of downstream analytics products.

Required Qualifications, Capabilities, and Skills

Hold a Master's degree in IT, Computer Science, MIS, Operations Research, or related field plus 3 years of relevant experience, or hold a Bachelor's degree in the same fields plus 5 years of relevant experience.
Demonstrate advanced SQL capability, including complex joins, performance tuning, and incremental logic.
Apply strong data modeling expertise across grains, facts/dimensions, conformed dimensions, SCDs, and metric design.
Build or operate a semantic layer or metrics framework to standardize KPI logic and definitions.
Model semi-structured data (e.g., JSON) and integrate NoSQL sources for analytics use cases.
Use Snowflake and/or Databricks effectively in an analytics engineering context and apply practical Python for workflow automation and validation.
Practice strong stakeholder partnership and documentation discipline to drive clarity, correctness, and measurable outcomes.

Preferred Qualifications, Capabilities, and Skills

Leverage experience with testing and documentation frameworks for analytics engineering.
Apply familiarity with BI consumption patterns and tooling concepts (e.g., Tableau, Sigma, Looker).
Utilize orchestration tooling knowledge (e.g., Airflow, Dagster, ADF) with an SLA and reliability mindset.
Implement observability practices such as logging, alerting, and operational runbooks for data products.
Optimize cost and performance trade-offs through pragmatic platform tuning and design decisions.