Role:Data Engineer Lead
Location:Melbourne
Duration:Permanent
Skills to be looked
Mandatory Skills
Microsoft Azure (DataLake, ADB, ADF, ADLS, Functions, Synapse etc )
Hadoop, Spark/PySpark / Python
SQL, SQL DataWarehouse
Knowledge in MS Fabric
Azure Devops , CI/CD and Github Actions, Dockers/Kubernetes
Azure Certifications
Exposure to any ETL tools
Coding Skill (MANDATORY)
Knowledge on Financial / Investment domain
Communication, Articulation & Attitude
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 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
- 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 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