Senior Data Engineer – Analyst / Manager

Role Overview

• Monitor and improve data quality by designing and implementing automated validation rules, performing ongoing data profiling, and executing data cleansing routines to ensure accuracy, completeness, and reliability.
• Develop, maintain, and continuously refine comprehensive documentation covering data pipelines, data models, solution architecture, and end-to-end data flows to support transparency, scalability, and knowledge sharing.
• Diagnose, troubleshoot, and resolve complex data pipeline failures, integration issues, and system performance bottlenecks, ensuring high availability and optimal performance across data platforms.
• Proactively evaluate and adopt emerging Azure data services, industry best practices, and modern engineering patterns to enhance platform capability, security, and efficiency.
• Collaborate closely with business stakeholders, data analysts, engineers, and product teams to gather requirements, translate them into technical solutions, and deliver robust, scalable, and high-quality data products.
• Implement CI/CD practices and Infrastructure as Code (e.g., Terraform/Bicep) for deploying and maintaining scalable data infrastructure.
• Design and optimise data pipelines using Azure services such as Data Factory, Databricks, Synapse, or Event Hub.
• Ensure data governance by enforcing metadata standards, lineage tracking, and access controls.

Requirements

• Minimum 5 years’ experience as a Data Engineer with a strong focus on Azure cloud data services, ideally within a professional services or consultancy environment.
• Hands-on experience with Data Governance and Management tooling (for example, Informatica, Collibra, etc), including data integration, workflow orchestration, and performance optimisation.
• Proven ability to design, build, and optimise scalable, secure data pipelines using Azure Data Factory and complementary Azure services such as Databricks, Synapse Analytics, Data Lake Storage, and Event Hub.
• Strong documentation practices, with the ability to produce clear and maintainable technical documentation covering data processes, architectures, models, and data flows.
• Demonstrated experience implementing data governance and metadata management frameworks using Microsoft Purview, ensuring data quality, compliance, lineage, and security controls.
• Experience leading and executing data migration initiatives, ensuring data integrity, consistency, and reconciliation across legacy systems and Azure cloud platforms.
• Strong capability in establishing and managing data quality processes, including automated validation rules, profiling, monitoring, and data cleansing to maintain trustworthy data assets.
• Familiarity with AWS and Google Cloud Platform (GCP), enabling support for hybrid or multi-cloud architectures where required.
• Proficiency in SQL, Python, or Spark for data transformation and complex logic development.
• Experience with DevOps practices and Infrastructure as Code (e.g., Terraform, Bicep, GitHub Actions, Azure DevOps).
• Understanding of data modelling (dimensional & relational) and modern data architectures such as data lakehouse, event-driven, or ETL-based patterns.

Tech Stack

• AWS
• Azure
• Cloud
• ETL
• Google Cloud Platform
• Informatica
• Python
• Spark
• SQL
• Terraform

Benefits

• Life & income protection
• Sonder/EAP/Headspace
• 15 days’ paid sick leave
• Group-rate health insurance (eligibility applies)
• Flexible working
• Supportive coaching culture
• Purchase up to two extra weeks’ annual leave
• Two recognition days provided each year
• Annual summer shutdown period
• Paid parental leave for all parents with flexible options and financial planning support
• Inclusive networks
• Paid volunteering leave
• Discretionary bonus opportunities
• Generous referral bonuses
• Retail discounts & deals