TECHNICAL LEAD L1

The purpose of this role is to facilitate application solutions by developing and reviewing module-level codes, creating replication patterns, performing root cause analysis to identify recurring issues and collaborating with internal and external stakeholders to ensure stable, well-documented deliverables that meet business objectives.

Areas of responsibility

Gathering of requirements-Participate in gathering requirements for specific modules and ensure clear, structured documentation. Work across multiple business processes to capture linkages, dependencies, and required changes.

Solution Design-Facilitate creation of application solution designs for a specific module under the guidance of the Project Manager, ensuring alignment with business requirements and technical standards.

Coding and Configuration-"Review the developed codes, resolve technical queries of the team for the assigned module and create consistent replication patterns, to ensure that the developed code aligns with the project standards.Collaborate with project managers through all phases of software development life cycle."

Perform root-cause analysis to identify and troubleshoot recurring technical issues. Modify software codes to resolve errors, adapt to new hardware and software, enhance performance, and upgrade interfaces."

Implementation-"Collaborate with technical teams to validate configurations, facilitate integration of new applications, and address dependencies during deployment. Prepare user training documents and related frameworks to ensure smooth adoption new applications and minimize transition risks."

Experience – 15+ years

Location – Melbourne

Client – AusSuper

Questions to be asked while sourcing:

How many years of experience do you have in Azure Data Engineering?

What is the peak team size you have managed?

Have you handled multiple stakeholders across business and technology teams?

Have you worked extensively with Azure Data Factory (ADF)?

Do you have hands-on experience with Azure Synapse Analytics?

Have you worked with Microsoft Fabric?

Do you have strong hands-on experience with PySpark and Python?

Have you designed and delivered enterprise-scale data platforms from scratch?

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

Job Description:

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 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.