Data Engineer

Full-time, Direct Hire

Remote - East Coast Preferred

Our client is an established logistics and industrial services company seeking a

Mid-Level Data Engineer

. In this role, you will modernize and scale data infrastructure across operations, finance, and business intelligence, converting raw operational data into trusted, scalable analytics assets.

Ideal candidates will have a background in industrial environments as an individual contributor and are passionate about flawless data.

• Role Type: Mid-Level Data Engineer (3–6 years experience)
• Core Tech Stack: Azure (Data Factory, Data Lake, Databricks), SQL, Power BI
• Domain: Fleet maintenance, supply chain, and field service operations

Core Responsibilities

• Data Pipelines \& ETL: Design, build, and maintain production-grade pipelines (ADF, Databricks, SQL) to ingest data from ERP, CRM, and financial systems.
• Data Modeling: Build optimized dimensional models, star schemas, and data marts within Azure Data Lake and data warehouses.
• BI Integration: Prepare and optimize trusted datasets, semantic models, and queries for high-performing Power BI dashboards.
• Data Quality \& Governance: Implement validation checks, resolve data integrity issues, and fully document pipelines and business logic.
• Performance Tuning: Monitor and optimize SQL queries, pipeline processing times, and report responsiveness.

Required Qualifications

• Experience: 3–6 years of data engineering, ETL development, or BI engineering experience.
• Education: Bachelor’s degree in CS, IT, Data Analytics, Engineering, or equivalent experience.
• SQL Mastery: Advanced proficiency in SQL (query optimization, stored procedures, joins, and indexing).
• Cloud \& Pipeline Tools: Hands-on experience building production pipelines using Azure Data Factory, Azure Databricks, SSIS, or Python.
• Data Modeling: Solid understanding of dimensional modeling and data warehouse architecture.
• Power BI: Experience preparing datasets, managing refresh schedules, and supporting dashboards.
• Soft Skills: Ability to gather requirements from business stakeholders and translate them into data solutions.

Preferred Qualifications

• Industry Experience: Background in transport, logistics, fleet maintenance, distribution, or field/industrial services.
• Advanced Tech: Experience with Python, PySpark, Spark SQL, Delta Lake, Synapse, Fabric, or Snowflake.
• Business Systems: Experience integrating data from Microsoft Dynamics 365 or specialized industrial ERP platforms.
• Data Types: Familiarity with operational data (work orders, asset tracking, inventory, labor, billing, and customer contracts).
• Integrations: Experience with APIs, SFTP, and flat-file ingestion.

Technical Environment Summary

• Cloud/Data Platforms: Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Synapse, Microsoft Fabric, Snowflake
• Languages \& BI: SQL, Python, PySpark, Power BI (DAX, semantic models)
• Target Systems: Microsoft Dynamics 365, specialized industrial ERPs, CRM, and APIs
• Workflows: Git, DevOps, automated monitoring, and alerting tools