https://JOBS.THEMORTONWAY.COM/ en-us Data Warehouse Developer to support the Data Strategy initiative and help build a modern, enterprise grade data platform for our client. This role focuses on designing, developing, and optimizing data pipelines and warehouse structures using AWS Glue, Snowflake, and Snowpipe. You will be responsible for transforming raw, disparate data into reliable, scalable, and well governed datasets that power analytics, reporting, and operational decision making across the agency. This role is FULLY ONSITE in North Chesterfield, VA.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines using AWS Glue, including Glue Jobs, Workflows, Crawlers, and Catalog integration.
• Develop and optimize Snowflake data models, schemas, and warehouse structures to support enterprise reporting and analytics.
• Implement and manage Snowpipe for continuous data ingestion from structured and semi structured sources.
• Collaborate with internal and external teams to understand data requirements, source system structures, and integration needs.
• Build scalable, secure, and high performance data ingestion and transformation processes aligned with best practices.
• Perform data profiling, data quality assessments, and root cause analysis for data issues across complex datasets.
• Support data migration activities, including mapping, cleansing, validation, and reconciliation.
• Develop and maintain documentation for data pipelines, data models, and operational processes.
• Work closely with business stakeholders, SMEs, and technical teams to translate requirements into robust data engineering solutions.
• Ensure compliance with data governance, security, and privacy standards across all data assets.
• Optimize Snowflake performance through clustering, partitioning, caching, and query tuning.
• Support ad hoc data engineering requests related to new integrations, data transformations, or enhancements.

Qualifications

• Proven experience as a Data Warehouse Developer, Data Engineer, or similar role.
• Hands on expertise with AWS Glue, including Glue Studio, Glue Jobs (PySpark/Python), Glue Catalog, and Glue Workflows.
• Strong experience with Snowflake, including schema design, Snowflake SQL, performance tuning, and data sharing.
• Practical experience implementing Snowpipe for automated ingestion from cloud storage.
• Strong SQL skills and experience working with large scale relational and cloud based databases.
• Proficiency in Python for ETL/ELT development and automation.
• Solid understanding of data modeling, data warehousing concepts, and ETL best practices.
• Experience with data quality, data validation, and data reconciliation processes.
• Ability to analyze complex data structures and troubleshoot data pipeline issues with precision.
• Strong communication skills and ability to collaborate with cross functional teams.
• Proficiency with Microsoft Office tools, especially Excel, for data validation and documentation.

Education & Experience

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Relevant certifications (AWS, Snowflake) are a plus.

]]> Fri, 13 Mar 2026 00:00:00 EDT 0 Foundational Analytics | dbt | Snowflake | High-Impact IC Role

A high-growth company is hiring a Senior Data Analytics Engineer to build the data foundation that powers trustworthy reporting, self-serve insights, and data-driven decision-making across the organization.

This is a ground-floor opportunity to own the core analytics engineering layer end-to-end — from defining foundational metrics and scalable data models to implementing best practices that will support long-term growth.

This is a senior individual contributor role where you’ll lead through technical ownership, influence, and execution while setting standards future hires will build upon.

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What You’ll Do Build the Data Foundation

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  Execute the analytics engineering roadmap, prioritizing high-leverage data initiatives
  
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  Design and implement a single source of truth using scalable data models (dimensional modeling, star schemas, modular marts)
  
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  Develop canonical business definitions and standardized metrics across teams
  
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  Manage and evolve a modern analytics stack (dbt, Snowflake, Git, CI/CD workflows)
  
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  Establish best practices for modeling, testing, documentation, naming conventions, and dataset ownership
  
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  Improve trust in data through quality checks, observability, and clear guidance on trusted datasets
  
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  Partner cross-functionally with Product, Engineering, Finance, and GTM to deliver impactful data solutions
  

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Enable Self-Serve & Decision-Making

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  Build curated datasets and semantic-friendly layers that support consistent BI and reporting
  
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  Develop dashboards and analytics tools that empower stakeholders to self-serve confidently
  
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  Translate ambiguous business questions into structured, scalable data products (not one-off analyses)
  
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  Communicate analytical findings clearly and provide actionable recommendations
  

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Lead Through Technical Ownership

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  Serve as the analytics engineering voice in architectural and technical decisions
  
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  Drive cross-functional projects from discovery through delivery
  
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  Promote data literacy through documentation, metric definitions, and enablement
  
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  Collaborate with product leaders during discovery to identify high-impact data opportunities
  

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What We’re Looking For Analytics Engineering & Modeling Expertise

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  5–8+ years in analytics engineering, data engineering, BI, or related roles
  
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  Advanced SQL proficiency and experience with modern cloud warehouses (Snowflake preferred)
  
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  Strong hands-on experience with dbt (or similar frameworks), including modular design, testing, and documentation
  
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  Deep experience designing scalable data models (star schemas, canonical metrics, shared dimensions)
  
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  Experience supporting reliable reporting via BI tools (Looker, Tableau, Mode, etc.)
  
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  Working knowledge of Python for scripting and automation
  

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Engineering Rigor & End-to-End Ownership

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  Experience owning pipelines from ingestion through BI consumption
  
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  Familiarity with Git workflows and CI/CD practices for analytics code
  
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  Experience implementing data quality and reliability frameworks (dbt tests, monitoring, SLAs, etc.)
  
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  Strong understanding of modern data architecture tradeoffs and scaling strategies
  

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Business Partnership & Senior IC Capabilities

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  Proven ability to translate vague business needs into structured data solutions
  
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  Strong communication skills and ability to align stakeholders on definitions and outcomes
  
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  Excellent prioritization skills, focusing on high-impact work
  
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  Comfortable operating in ambiguity while maintaining quality and trust
  

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Bonus Experience

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  Semantic modeling layers (LookML or similar)
  
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  Workflow orchestration tools (Airflow, Dagster, Hevo, etc.)
  
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  Startup or high-growth tech environments
  
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  Data cataloging or metadata management tools
  
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  Statistical analysis or experimentation experience
  
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  Exposure to AI/ML applications
  

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Why This Role Is Compelling
This is a rare opportunity to define and scale the analytics function at a growing organization. You’ll have the autonomy to establish standards, influence tooling decisions, and make an immediate impact on business outcomes.

If you thrive at the intersection of strategy and hands-on execution — and enjoy building scalable systems from the ground up — this role offers meaningful ownership and visibility.
]]> Fri, 06 Mar 2026 00:00:00 EST 0