Data Engineer 

Job Type: Contract-to-Hire
Location: Remote (Eastern/Central time zones preferred)

Summary

As a Data Engineer, your position involves designing, developing, and maintaining data pipelines and solutions using Databricks, SQL, and PySpark. Working within a collaborative Data & Analytics team, you will transform enterprise and business-specific data into reliable, accessible datasets that support business operations, reporting, analytics, and data science initiatives.

This is a hands-on development role focused on building new pipelines, modernizing existing processes, improving data quality, and contributing to engineering best practices. You will work closely with data science, analytics, and business stakeholders to understand requirements and deliver effective data solutions.

Design, Build, and Maintain Data Pipelines / Solutions (60%)

• Design, develop, test, and maintain data pipelines using Databricks, SQL, and PySpark.

• Modernize existing pipelines and improve performance, reliability, and maintainability.

• Develop and manage data transformations and reporting-layer datasets to support business analytics and reporting.

• Monitor, troubleshoot, and resolve pipeline issues to ensure accurate and timely data delivery.

• Create and maintain technical documentation, including data mappings, lineage, and data dictionaries.

• Collaborate with the team on solution design, development standards, and continuous improvement initiatives.

Collaborate with Stakeholders and Ensure Data Quality (30%)

• Partner with business stakeholders and analytics teams to understand data requirements and develop solutions that support business needs.

• Implement data quality checks, validation processes, and reconciliation procedures to ensure data accuracy and integrity.

• Troubleshoot data integration issues and identify opportunities to improve existing processes.

• Communicate project progress, technical challenges, and potential solutions to team members and stakeholders.

• Take ownership of assigned development tasks while collaborating with the broader team.

Continuous Improvement and Collaboration (10%)

• Contribute to improving data engineering practices, coding standards, and development processes.

• Stay current with relevant data engineering technologies and apply new techniques when appropriate.

• Collaborate with team members to support analytics, automation, and future data initiatives.

• Participate in team discussions, knowledge sharing, and continuous improvement efforts.

The Experience, Skills and Abilities Needed

Required:

• 3+ years of hands-on data engineering or related development experience.

• Strong hands-on experience with Databricks, including developing and maintaining production data pipelines.

• Proficiency in SQL and PySpark for data transformations, processing, and pipeline development.

• Experience with ETL/ELT development, data warehousing, and data integration.

• Experience implementing data quality checks, testing, validation, and troubleshooting.

• Familiarity with data modeling and developing datasets for analytics and reporting.

• Experience working with cloud-based data environments.

• Strong problem-solving skills and ability to independently manage assigned development tasks.

• Effective communication skills and experience collaborating with technical and business stakeholders.

Preferred:

• Experience with Microsoft Azure, including Azure Data Factory.

• Experience with Snowflake, Delta Lake, and Databricks notebooks.

• Familiarity with Azure DevOps, Jira, Git, or similar development tools.

• Experience modern