Data Engineer

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)
• 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.
• 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.

• Target Systems:
  Microsoft Dynamics 365, specialized industrial ERPs, CRM, and APIs
• Workflows:
  Git, Dev Ops, automated monitoring, and alerting tools