Lead Data Engineer

Job Description

Mandatory
\n Skill Set: SQL + Python + PySpark + Azure Synapse

\n

\n

Role Overview

\n

We are seeking a highly
\n experienced Lead Data Engineer to drive the strategy, architecture,
\n delivery, and optimization of enterprise-scale data platforms on Microsoft
\n Azure. The ideal candidate will combine deep technical expertise with strong
\n leadership, stakeholder management, and delivery governance capabilities to
\n build scalable, secure, and cost-efficient data solutions.

\n

\n

Must-Have Skills

\n

\n
• Strong
  \n expertise in SQL, Python, and PySpark
  
\n
• Extensive
  \n experience with Azure Data Factory (ADF) and Azure Synapse Analytics .
  
\n
• Hands-on
  \n experience with Delta Lake architecture and modern data lakehouse
  \n implementations.
  
\n
• Advanced
  \n knowledge of Data Modeling and Data Warehousing concepts.
  
\n
• Strong
  \n exposure to the Microsoft Fabric ecosystem.
  
\n
• Proven
  \n expertise in designing cloud-native data architectures and
  \n enterprise-scale solutions.
  
\n
• Strong design thinking and problem-solving capabilities.
  
\n
• Working
  \n knowledge of CI/CD pipelines and DevOps practices .
  
\n
• Experience
  \n in cloud cost optimization, performance tuning, and resource governance .
  
\n

\n

\n

Key Responsibilities

\n

\n
• Lead
  \n and own the end-to-end delivery of enterprise data platforms ,
  \n including architecture, development, deployment, and optimization.
  
\n
• Define
  \n and drive the data platform roadmap , ensuring alignment with
  \n business objectives and strategic priorities.
  
\n
• Architect
  \n and govern scalable data pipelines, data models, data warehouses, and
  \n lakehouse solutions using Azure services.
  
\n
• Provide
  \n technical leadership to Data Engineering teams through design reviews,
  \n code reviews, and implementation of engineering best practices.
  
\n
• Drive
  \n the adoption and implementation of Microsoft Fabric, APIs, Azure
  \n Functions, and Python-based solutions .
  
\n
• Ensure
  \n platform scalability, reliability, security, and operational excellence
  \n while optimizing cloud costs.
  
\n
• Establish
  \n and enforce data governance, data quality, security, and compliance
  \n standards .
  
\n
• Implement
  \n and drive CI/CD, DevOps, and Agile delivery practices across the
  \n data engineering landscape.
  
\n
• Collaborate
  \n with business stakeholders, architects, and technology teams to translate
  \n business requirements into scalable technical solutions.
  
\n
• Mentor,
  \n coach, and develop Data Engineering talent, fostering a culture of
  \n continuous learning and innovation.
  
\n
• Leverage GitHub Copilot and AI-assisted engineering tools to improve productivity
  \n and solution quality.
  
\n
• Drive
  \n innovation by evaluating emerging technologies and identifying
  \n opportunities for platform modernization.
  
\n

\n

\n

Experience

\n

\n
• 10+
  \n years of overall IT experience, including 10+ years in Data Engineering .
  
\n
• Minimum 5+ years of leadership experience managing large-scale Data
  \n Engineering programs and teams.
  
\n
• Proven
  \n track record of leading cross-functional teams and delivering complex
  \n enterprise data transformation initiatives.
  
\n
• Experience
  \n building, hiring, and scaling high-performing Data Engineering teams.
  
\n
• Experience
  \n working within multi-vendor and globally distributed delivery
  \n environments .
  
\n
• Strong
  \n experience in stakeholder management, delivery governance, and
  \n executive-level communication.
  
\n

\n

\n

Preferred Skills

\n

\n
• Experience
  \n building and managing enterprise APIs and Azure Function Apps .
  
\n
• Exposure
  \n to framework-based data engineering development approaches .
  
\n
• Experience
  \n in solution architecture, stakeholder engagement, and delivery
  \n governance .
  
\n
• Azure
  \n certifications such as:
  
\n
\n
• Azure
  \n Data Engineer Associate
  
\n
• Azure
  \n Solutions Architect Expert
  
\n
\n
• Familiarity
  \n with MLOps, Data Science, and AI-driven analytics solutions .
  
\n
• Hands-on
  \n experience with Power BI and enterprise reporting platforms.
  
\n
• Experience
  \n leveraging AI and Generative AI capabilities within Data Engineering
  \n ecosystems .
  
\n

\n

\n

Key Leadership Traits

\n

\n
• Strong
  \n ownership mindset with a focus on accountability and business outcomes.
  
\n
• Excellent
  \n communication, stakeholder management, and influencing skills.
  
\n
• Ability
  \n to balance technical leadership with delivery and people management
  \n responsibilities .
  
\n
• Strategic
  \n thinker with a strong focus on execution excellence.
  
\n
• Strong
  \n conflict resolution and cross-functional collaboration skills.
  
\n
• Adaptability
  \n and resilience in fast-paced, evolving environments.
  
\n
• Passion
  \n for mentoring teams and fostering a culture of innovation and continuous
  \n improvement.
  
\n

\n