Data Engineer (Data Platforms, ETL & Data Modeling)

Data Engineer (Data Platforms, ETL & Data Modeling)

Our client is hiring a Data Engineer for a full-time, direct hire position. We're looking for a hands-on Data Engineer who enjoys building data pipelines, modeling complex data, and solving messy data challenges in cloud environments. This is a data engineering role focused on platform, pipeline, and data architecture work—not a reporting or BI-focused position.

Job Type: Full-Time, Direct Hire

Location: Remote

Compensation: This job is expected to pay about $130,000-150,000 plus benefits

No Visa Sponsorship Available for this role

What You'll Do:

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows that power business-critical analytics and applications.
• Develop and optimize complex SQL queries, data models, and transformation processes to improve data quality, performance, and reliability.
• Work with cloud data platforms such as Microsoft Fabric, Snowflake, or Databricks to support modern data engineering initiatives.
• Partner with business and technical stakeholders to understand data requirements, troubleshoot issues, and deliver actionable data solutions.
• Develop and maintain data integrations using APIs and other data exchange methods across internal and external systems.
• Monitor, troubleshoot, and continuously improve data platform performance, availability, and operational efficiency.
• Lead technical initiatives, perform code reviews, and contribute to engineering best practices, documentation, and mentoring efforts.
• Support the reporting and analytics teams by ensuring clean, trusted, and well-structured data is available for downstream consumption.

What Gets You the Job:

• 5+ years of hands-on data engineering experience building and supporting production data pipelines.
• Advanced SQL skills with the ability to write, optimize, and troubleshoot complex queries.
• Strong experience with data modeling, ETL/ELT development, and data transformation best practices.
• Experience working with cloud-based data platforms such as Microsoft Fabric, Snowflake, Databricks, or similar technologies.
• Proficiency in Python for data engineering, automation, and data processing tasks.
• Experience with data orchestration tools such as Azure Data Factory, Airflow, or similar platforms.
• Familiarity with REST APIs and data integration concepts.
• Strong troubleshooting and problem-solving skills with the ability to work independently in ambiguous or fast-changing environments.
• Experience using Git and modern software development best practices.
• Ability to lead projects, mentor team members, and take ownership of delivering high-quality data solutions.

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