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.

Robust 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

#J-18808-Ljbffr

📌 Data Engineer (Port Phillip City)
🏢 Renaissance InfoSystems
📍 Port Phillip City