Senior Data Engineer (1143847)

The Judge Group

Dallas (TX)

Hybrid

USD 120,000 - 130,000

Full time

14 days+

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Job summary

The Judge Group seeks a Senior Data Engineer to design, build, and scale modern data platforms for analytics and AI initiatives in Dallas. The role focuses on robust data ingestion, transformation, and trusted datasets across enterprise environments.

The ideal candidate has strong cloud data engineering experience, Snowflake, Fivetran, dbt, AWS Glue, Python, SQL, and PySpark expertise, with a drive to optimize pipelines and enable data products at scale.

Qualifications

Bachelor's degree or equivalent practical experience in a technical field.
7–10 years of experience in Data Engineering, Data Integration, or related disciplines.
Experience designing and developing enterprise-scale data pipelines and ETL/ELT solutions.
Hands-on with Snowflake, Fivetran, dbt, AWS Glue, Python, SQL, PySpark.
Experience with data warehousing, dimensional modeling, and data lake architectures.
Experience implementing data quality, monitoring, and validation frameworks.
Strong software engineering practices, version control, and CI/CD.

Responsibilities

Design, develop, and maintain scalable data pipelines and data models within Snowflake.
Build and manage data ingestion frameworks using Fivetran and other cloud-native integration technologies.
Develop and optimize ETL/ELT workflows using dbt, AWS Glue, Python, and PySpark.
Architect and support data lake and data warehouse solutions on AWS and Snowflake.
Perform source-to-target mapping and support enterprise data migration and modernization initiatives.
Implement data quality, validation, reconciliation, and monitoring processes to ensure data reliability and accuracy.
Develop reusable frameworks, automation capabilities, and standardized pipeline patterns to improve engineering efficiency.
Partner with architects, analytics teams, and business stakeholders to deliver scalable and trusted data products.
Prepare, transform, and manage datasets that support advanced analytics, machine learning, and generative AI use cases.
Apply DataOps, CI/CD, governance, security, and operational best practices across the data ecosystem.
Troubleshoot performance issues and continuously improve the scalability, reliability, and maintainability of data solutions.

Education

Bachelor's degree in CS/IT/Engineering or equivalent

Tools

Snowflake

Fivetran

dbt

AWS Glue

Python

SQL

PySpark

Job description

Location: Dallas, TX

Salary: $120,000.00 USD Annually - $130,000.00 USD Annually

Description: You must be able to accept w2 employment without sponsorship now or in the future and be able to attend an onsite interview in Dallas and live locally to Dallas for a hybrid position.

Senior Data Engineer

About the Role

We are seeking a Senior Data Engineer to design, build, and scale modern data platforms that enable analytics, data products, and AI initiatives across the enterprise. In this role, you will develop robust data ingestion and transformation frameworks, optimize data pipelines, and deliver trusted, high-quality datasets that support business decision-making and innovation.

The ideal candidate has strong experience in cloud-based data engineering, data warehousing, and large-scale ETL/ELT development, along with expertise in Snowflake, Fivetran, dbt, AWS Glue, Python, and SQL.

Responsibilities

Design, develop, and maintain scalable data pipelines and data models within Snowflake.
Build and manage data ingestion frameworks using Fivetran and other cloud-native integration technologies.
Develop and optimize ETL/ELT workflows using dbt, AWS Glue, Python, and PySpark.
Architect and support data lake and data warehouse solutions on AWS and Snowflake.
Perform source-to-target mapping and support enterprise data migration and modernization initiatives.
Implement data quality, validation, reconciliation, and monitoring processes to ensure data reliability and accuracy.
Develop reusable frameworks, automation capabilities, and standardized pipeline patterns to improve engineering efficiency.
Partner with architects, analytics teams, and business stakeholders to deliver scalable and trusted data products.
Prepare, transform, and manage datasets that support advanced analytics, machine learning, and generative AI use cases.
Apply DataOps, CI/CD, governance, security, and operational best practices across the data ecosystem.
Troubleshoot performance issues and continuously improve the scalability, reliability, and maintainability of data solutions.

Minimum Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent practical experience.
7 to 10 years of experience in Data Engineering, Data Integration, or related disciplines.
Experience designing and developing enterprise-scale data pipelines and ETL/ELT solutions.
Hands-on experience with:
- Snowflake
- Fivetran
- dbt
- AWS Glue
- Python
- SQL
- PySpark
Experience with data warehousing, dimensional modeling, and data lake architectures.
Experience implementing data quality, monitoring, and validation frameworks.
Strong understanding of software engineering best practices, version control, and CI/CD methodologies.

Preferred Qualifications

Experience supporting machine learning, AI, or generative AI data pipelines.
Experience with DataOps practices and automated data platform operations.
Knowledge of infrastructure automation and cloud-native architecture patterns.
Experience optimizing large-scale data processing workloads and query performance.
Ability to influence technical direction and collaborate effectively across engineering, analytics, and business teams.
Strong problem-solving, communication, and stakeholder management skills.

Technical Expertise

Data Engineering & Analytics