Role Overview

We are seeking a highly experienced Senior 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 contemporary 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

· 15+ years of overall IT experience, including 15+ years in Data Engineering.

· Minimum 10+ 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:

o Azure Data Engineer Associate o 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.

📌 Data Engineer (Melbourne)
🏢 Wipro
📍 Melbourne