What are the responsibilities and job description for the Data Engineer position at TECHEAD?
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.
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
- 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.
- 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.
- 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.
- 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