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Data Engineer
TECHEAD
- New York, New York, United States
- New York, New York, United States
About
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
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.
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
Target Systems: Microsoft Dynamics 365, specialized industrial ERPs, CRM, and APIs
Workflows: Git, DevOps, automated monitoring, and alerting tools
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Languages
- English
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