Lead Azure Data Engineer

Data Architecture & Design

• Lead the end-to-end and design of data platforms using Microsoft Fabric, Synapse Analytics, and ADF.
• Define and implement data models, warehouse/lakehouse designs, and normalization strategies to support manufacturinganalytics.
• Establish data integration patterns, ingestion pipelines, and governance frameworks across structured, semi-structured, and unstructured data sources.
• Drive adoption of best practices in SQL, PySpark, and data lakehouse technologies.
• Should have working experience in Databricks

Technical Leadership & Guidance

• Partner with data engineers, BI developers, and business stakeholders to translate manufacturing requirements into scalable data solutions.
• Lead the team and provide reviews, performance tuning, and optimization guidance across SQL, PySpark, and Synapse workloads.
• Mentor and guide teams in building efficient pipelines, ELT/ETL frameworks, and reusable components.
• Establish standards for security, compliance, metadata management, and lineage tracking.

Analytics & Reporting Enablement

• Lead & Design enterprise BI solutions in Power BI, ensuring performance, usability, and self-service capabilities.
• Define semantic models and KPIs relevant to the manufacturing domain (OEE, downtime, yield, energy efficiency, carbon footprint, cost tracking, etc.).
• Collaborate with business teams to operationalize advanced analytics, predictive maintenance, and digital twin use cases.

Manufacturing Domain Expertise

• Leverage deep knowledge of manufacturing processes, MES/ERP integration, IoT/sensor data, supply chain, and production metrics.
• Map data flows across shop-floor systems, quality systems, energy/fuel consumption, and sustainability reporting.
• Good understanding of how data architecture can drive efficiency, reduce downtime, and optimize operations.

Preferred qualifications:

• Knowledge of data governance, MDM, and data quality frameworks.
• Familiarity with cloud-native architecture (Azure ecosystem) and DevOps/DataOps practices.
• Strong communication skills to Lead the team and handle senior business and IT stakeholders.