We are seeking a highly experiencedSenior Lead Data Engineerto 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
Robust expertise inSQL, Python, and PySpark.
Extensive experience withAzure Data Factory (ADF)andAzure Synapse Analytics.
Hands-on experience withDelta Lake architectureand modern data lakehouse implementations.
Advanced knowledge ofData ModelingandData Warehousingconcepts.
Strong exposure to theMicrosoft Fabricecosystem.
Proven expertise in designingcloud-native data architecturesand enterprise-scale solutions.
Strongdesign thinkingand problem-solving capabilities.
Working knowledge ofCI/CD pipelines and DevOps practices.
Experience incloud cost optimization, performance tuning, and resource governance.
Key Responsibilities
Lead and own theend-to-end delivery of enterprise data platforms, including architecture, development, deployment, and optimization.
Define and drive thedata platform roadmap, ensuring alignment with business objectives and strategic priorities.
Architect and govern scalabledata pipelines, data models, data warehouses, and lakehouse solutionsusing 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 ofMicrosoft Fabric, APIs, Azure Functions, and Python-based solutions.
Ensure platform scalability, reliability, security, and operational excellence while optimizing cloud costs.
Establish and enforcedata governance, data quality, security, and compliance standards.
Implement and driveCI/CD, DevOps, and Agile delivery practicesacross 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.
LeverageGitHub Copilot and AI-assisted engineering toolsto improve productivity and solution quality.
Drive innovation by evaluating emerging technologies and identifying opportunities for platform modernization.
Experience
15+ yearsof overall IT experience, including15+ years in Data Engineering.
Minimum15+ years of leadership experiencemanaging 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 withinmulti-vendor and globally distributed delivery environments.
Strong experience in stakeholder management, delivery governance, and executive-level communication.
Preferred Skills
Experience building and managingenterprise APIs and Azure Function Apps.
Exposure toframework-based data engineering development approaches.
Experience insolution architecture, stakeholder engagement, and delivery governance.
Azure certifications such as:
Azure Solutions Architect Expert
Familiarity withMLOps, Data Science, and AI-driven analytics solutions.
Hands-on experience withPower BIand enterprise reporting platforms.
Experience leveragingAI and Generative AI capabilities within Data Engineering ecosystems.
Strong ownership mindset with a focus on accountability and business outcomes.
Excellent communication, stakeholder management, and influencing skills.
Ability to balancetechnical 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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📌 Lead Data Engineer (Melbourne)
🏢 Wipro
📍 Melbourne