Key Responsibilities:

· Pipeline Development: Build and maintain robust ETL/ELT pipelines using Databricks (PySpark/Spark SQL), and related Azure data services. Ensure pipelines handle batch and streaming workloads reliably at scale.
· Legacy Modernisation: Lead the migration of legacy data pipelines to modern cloud-native solutions on Azure and Databricks. Define migration strategies, manage cutover plans, and ensure zero data loss during transition.
· Data Quality & Governance: Establish and enforce data quality frameworks, validation rules, and monitoring across all pipelines. Implement data lineage tracking, cataloguing (Unity Catalog), and access governance in line with organisational policies.
· Data Modelling & Design: Design logical and physical data models for analytical and operational workloads. Define schemas, partitioning strategies, and optimisation patterns for performance and cost efficiency across Delta Lake and Azure SQL.
· Stakeholder Engagement: : Engage with the client’s Data & Analytics team on technical discussions, solution walkthroughs, and progress updates. Participate in requirement workshops and provide technical input to support estimation and planning.
· DevOps & Automation: Build and maintain CI/CD pipelines for data workloads using Azure DevOps. Implement automated testing for data pipelines, and deployment automation across environments.
· Mentorship & Standards: Review code, enforce engineering standards, and mentor offshore and onsite data engineers. Drive adoption of best practices for Spark, SQL, Python, testing, and version control across the team.

Location

Auckland

Job Function

TECHNOLOGY

Role

Engineer

Job Id

415414

Desired Skills

Automation Testing | Azure | DevOps