Analytics Engineer

David Weekley Homes•Houston, TX

9d•Onsite

About The Position

David Weekley Homes is seeking an Analytics Engineer to design, build, and deliver advanced analytics and AI-enabled solutions that turn our enterprise data, centered in Snowflake, into trusted, business-ready insights and decision support tools. Collaborate with data engineers to design and refine analytics-ready data models, transformations, and semantic layers in Snowflake. Contribute to data quality checks, validation logic, and usability standards for downstream analytics and AI use cases. Develop and apply statistical, predictive, and machine-learning techniques to business problems. Build and evaluate features, models, and analytical prototypes using Python, SQL, and Snowflake-native capabilities. Partner with internal teams or vendors to operationalize models and AI-driven insights into reports, dashboards, or lightweight applications. Support GenAI and retrieval-augmented (RAG) by preparing high-quality data, defining guardrails, and validating outputs for business use. Work directly with business stakeholders to translate business questions into analytical approaches. Communicate results to technical and non-technical audiences through visuals, summaries, and working prototypes. Follow standards for version control, documentation, and reproducibility. Contribute to data governance practices related to lineage, access controls, and responsible AI use. Coordinate with vendors and internal teams to ensure deliverables meet quality and business expectations

Requirements

5–7 years of experience in analytics engineering, advanced analytics, data science, or a closely related role.
Strong proficiency in Python and SQL, with experience building analytical workflows and models.
Hands-on experience working with Snowflake as an analytics platform.
Experience developing predictive or statistical models and translating results into business insights.
Comfort working closely with business partners to define problems, scope solutions, and deliver actionable outcomes.
Working knowledge of data governance, security concepts, and responsible data use.
Proven ability to collaboratively move analytical prototypes into repeatable, production-supported solutions.

Nice To Haves

Experience in homebuilding, construction, real estate, manufacturing, or related industries.
Exposure to GenAI or RAG-style analytics applications.
Familiarity with Snowflake-native advanced analytics or AI capabilities.
Experience collaborating with vendors or external partners on analytics or AI initiatives.

Responsibilities

design, build, and deliver advanced analytics and AI-enabled solutions
Collaborate with data engineers to design and refine analytics-ready data models, transformations, and semantic layers in Snowflake.
Contribute to data quality checks, validation logic, and usability standards for downstream analytics and AI use cases.
Develop and apply statistical, predictive, and machine-learning techniques to business problems.
Build and evaluate features, models, and analytical prototypes using Python, SQL, and Snowflake-native capabilities.
Partner with internal teams or vendors to operationalize models and AI-driven insights into reports, dashboards, or lightweight applications.
Support GenAI and retrieval-augmented (RAG) by preparing high-quality data, defining guardrails, and validating outputs for business use.
Work directly with business stakeholders to translate business questions into analytical approaches.
Communicate results to technical and non-technical audiences through visuals, summaries, and working prototypes.
Follow standards for version control, documentation, and reproducibility.
Contribute to data governance practices related to lineage, access controls, and responsible AI use.
Coordinate with vendors and internal teams to ensure deliverables meet quality and business expectations