Senior Snowflake Data Engineer

Plano, TX, US • Posted 19 hours ago • Updated 6 hours ago
Full Time
On-site
Fitment

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Job Details

Skills

  • Finance
  • Marketing Operations
  • Supply Chain Management
  • Production Support
  • Machine Learning (ML)
  • Advanced Analytics
  • Use Cases
  • Software Engineering
  • SQL
  • Analytical Skill
  • Modeling
  • Testing
  • Documentation
  • Continuous Integration
  • Continuous Delivery
  • Python
  • Data Processing
  • Cloud Computing
  • ELT
  • Data Warehouse Architecture
  • Git
  • Workflow
  • Code Review
  • Reporting
  • Incident Management
  • Computer Science
  • Data Engineering
  • Information Systems
  • Data Science
  • Snow Flake Schema
  • GitHub
  • Business Intelligence
  • Data Governance
  • Meta-data Management
  • Data Quality
  • KPI
  • Amazon Web Services
  • Amazon S3
  • Amazon RDS
  • Remote Desktop Services
  • Cloud Storage
  • Semantics
  • Analytics
  • Artificial Intelligence
  • Innovation
  • Continuous Improvement

Summary

Job Description

Senior Snowflake Data Engineer
Location: Plano, TX
Employment Type: Full-Time
Location: Onsite 4 days (Monday - Thursday)
Citizenship:
We are seeking a Senior Data Engineer to help build and scale a modern cloud data platform that powers analytics, reporting, machine learning, and future AI initiatives. This role is ideal for a hands-on data professional who enjoys creating trusted data products, improving data quality, and partnering with business leaders to turn complex data into reliable, business-ready insights.
In this role, you will design scalable data models, build and maintain analytics-ready datasets, support enterprise reporting, and help establish strong governance practices across the organization. You will work closely with teams across Finance, Marketing, Operations, Supply Chain, Digital, and other business functions to deliver data solutions that drive measurable business impact.
What You'll Do
  • Design, develop, and maintain scalable DBT models and analytics-ready datasets.
  • Build reusable dimensional, semantic, and enterprise data models.
  • Write and optimize complex SQL transformations across large datasets.
  • Develop Python-based tools for data quality, automation, validation, and platform operations.
  • Own data products and pipelines from design through production support.
  • Implement data quality checks, documentation, lineage, monitoring, and observability standards.
  • Partner with stakeholders to define KPIs, metrics, business definitions, and trusted data assets.
  • Support data governance initiatives, including metadata, ownership, stewardship, and certification.
  • Help prepare enterprise data assets for future AI, machine learning, and advanced analytics use cases.
Requirements
  • 7+ years of experience in Data Engineering, Analytics Engineering, Software Engineering, or a related field.
  • Strong SQL experience, including complex analytical transformations at scale.
  • Hands-on DBT experience, including modeling, testing, documentation, CI/CD, and deployment workflows.
  • Strong Python programming skills for data processing, automation, APIs, and tooling.
  • Experience designing dimensional, semantic, and analytics-focused data models.
  • Experience building and optimizing large-scale data pipelines and cloud-based data platforms.
  • Strong understanding of modern ELT practices and data warehouse architecture.
  • Experience with Git-based development workflows and code review processes.
  • Experience supporting BI, analytics, and self-service reporting environments.
  • Experience supporting production data environments, incident response, and operational troubleshooting.
  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.
Preferences
  • Experience with Snowflake, AWS, Airflow or Astronomer, Fivetran, RudderStack, GitHub, and modern BI platforms.
  • Experience with data governance tools such as Atlan, Collibra, or similar platforms.
  • Familiarity with metadata management, lineage, stewardship, and enterprise data quality practices.
  • Experience defining business metrics, KPI standards, and enterprise data definitions.
  • Exposure to AWS services such as S3, RDS, Lambda, or related cloud storage and processing technologies.
  • Interest in AI-enabled analytics, semantic layers, retrieval-based architectures, AI agents, or intelligent automation.
Why This Role
This is an opportunity to take ownership of high-impact data products, influence the future of a modern data platform, and help shape the foundation for analytics, governance, and AI-enabled capabilities. You will work in a collaborative environment that values ownership, innovation, continuous improvement, and practical execution.

Meet Your Recruiter

Logan Ridgley
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: bravo
  • Position Id: c36bf33f1be45e8361078fdfc993e8c9
  • Posted 19 hours ago
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