Job Description - Lead Data Engineer

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

 

Role Overview

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

 

Must-Have Skills

  • Strong
    expertise in SQL, Python, and PySpark

  • Extensive
    experience with Azure Data Factory (ADF) and Azure Synapse Analytics.

  • Hands-on
    experience with Delta Lake architecture and modern data lakehouse
    implementations.

  • Advanced
    knowledge of Data Modeling and Data Warehousing concepts.

  • Strong
    exposure to the Microsoft Fabric ecosystem.

  • Proven
    expertise in designing cloud-native data architectures and
    enterprise-scale solutions.

  • Strong design thinking and problem-solving capabilities.
  • Working
    knowledge of CI/CD pipelines and DevOps practices.

  • Experience
    in cloud cost optimization, performance tuning, and resource governance.

 

Key Responsibilities

  • Lead
    and own the end-to-end delivery of enterprise data platforms,
    including architecture, development, deployment, and optimization.

  • Define
    and drive the data platform roadmap, ensuring alignment with
    business objectives and strategic priorities.

  • Architect
    and govern scalable data pipelines, data models, data warehouses, and
    lakehouse solutions
    using Azure services.

  • Provide
    technical leadership to Data Engineering teams through design reviews,
    code reviews, and implementation of engineering best practices.

  • Drive
    the adoption and implementation of Microsoft Fabric, APIs, Azure
    Functions, and Python-based solutions
    .

  • Ensure
    platform scalability, reliability, security, and operational excellence
    while optimizing cloud costs.

  • Establish
    and enforce data governance, data quality, security, and compliance
    standards
    .

  • Implement
    and drive CI/CD, DevOps, and Agile delivery practices across the
    data engineering landscape.

  • Collaborate
    with business stakeholders, architects, and technology teams to translate
    business requirements into scalable technical solutions.

  • Mentor,
    coach, and develop Data Engineering talent, fostering a culture of
    continuous learning and innovation.

  • Leverage GitHub Copilot and AI-assisted engineering tools to improve productivity
    and solution quality.

  • Drive
    innovation by evaluating emerging technologies and identifying
    opportunities for platform modernization.

 

Experience

  • 10+
    years
    of overall IT experience, including 10+ years in Data Engineering.
  • Minimum 5+ years of leadership experience managing large-scale Data
    Engineering programs and teams.

  • Proven
    track record of leading cross-functional teams and delivering complex
    enterprise data transformation initiatives.

  • Experience
    building, hiring, and scaling high-performing Data Engineering teams.

  • Experience
    working within multi-vendor and globally distributed delivery
    environments
    .

  • Strong
    experience in stakeholder management, delivery governance, and
    executive-level communication.

 

Preferred Skills

  • Experience
    building and managing enterprise APIs and Azure Function Apps.

  • Exposure
    to framework-based data engineering development approaches.

  • Experience
    in solution architecture, stakeholder engagement, and delivery
    governance
    .

  • Azure
    certifications such as:

    • Azure
      Data Engineer Associate

    • Azure
      Solutions Architect Expert

  • Familiarity
    with MLOps, Data Science, and AI-driven analytics solutions.

  • Hands-on
    experience with Power BI and enterprise reporting platforms.

  • Experience
    leveraging AI and Generative AI capabilities within Data Engineering
    ecosystems
    .

 

Key Leadership Traits

  • Strong
    ownership mindset with a focus on accountability and business outcomes.

  • Excellent
    communication, stakeholder management, and influencing skills.

  • Ability
    to balance technical leadership with delivery and people management
    responsibilities
    .

  • Strategic
    thinker with a strong focus on execution excellence.

  • Strong
    conflict resolution and cross-functional collaboration skills.

  • Adaptability
    and resilience in fast-paced, evolving environments.

  • Passion
    for mentoring teams and fostering a culture of innovation and continuous
    improvement.



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