Note: The job is a remote job and is open to candidates in USA. TECHEAD is an established logistics and industrial services company celebrating over thirty-five years of heritage and accomplishments. They are seeking a Mid-Level Data Engineer to modernize and scale data infrastructure across operations, finance, and business intelligence, converting raw operational data into trusted, scalable analytics assets.
Responsibilities
- Design, build, and maintain production-grade pipelines (ADF, Databricks, SQL) to ingest data from ERP, CRM, and financial systems
- Build optimized dimensional models, star schemas, and data marts within Azure Data Lake and data warehouses
- Prepare and optimize trusted datasets, semantic models, and queries for high-performing Power BI dashboards
- Implement validation checks, resolve data integrity issues, and fully document pipelines and business logic
- Monitor and optimize SQL queries, pipeline processing times, and report responsiveness
- Beyond building the data foundation, this role has real room to expand into automation and AI work across the business
Skills
- 3–6 years of data engineering, ETL development, or BI engineering experience
- Bachelor's degree in CS, IT, Data Analytics, Engineering, or equivalent experience
- Advanced proficiency in SQL (query optimization, stored procedures, joins, and indexing)
- Hands-on experience building production pipelines using Azure Data Factory, Azure Databricks, SSIS, or Python
- Solid understanding of dimensional modeling and data warehouse architecture
- Experience preparing datasets, managing refresh schedules, and supporting dashboards
- In addition to pipeline and reporting experience, have the ability to speak to AI-enabled applications you've built at work or personally
- Ability to gather requirements from business stakeholders and translate them into data solutions
- Background in transport, logistics, fleet maintenance, distribution, or field/industrial services
- Experience with Python, PySpark, Spark SQL, Delta Lake, Synapse, Fabric, or Snowflake
- Experience integrating data from Microsoft Dynamics 365 or specialized industrial ERP platforms
- Familiarity with operational data (work orders, asset tracking, inventory, labor, billing, and customer contracts)
- Experience with APIs, SFTP, and flat-file ingestion
Company Overview