Senior Operations Analyst - Defence Analytics Lead

Chandler Macleod Group; Canberra; Hybrid; AUD 120,000 - 160,000; Full time

Job summary

INGRITY is seeking an experienced Lead Data Engineer to drive data ingestion, transformation and analytics solutions for a Federal Government context. The role emphasizes cloud-native architectures across Azure and Databricks, with a focus on secure, scalable data pipelines and governance.

You will lead cross-functional teams, mentor junior engineers and ensure high-quality data delivery for decision support.

Qualifications

• Five+ years of data engineering experience in cloud or government environments.
• Experience designing and maintaining ETL/ELT pipelines for large data sets.

Responsibilities

• Design, build and maintain data ingestion and transformation solutions.
• Lead data engineering across Azure Databricks and related services.
• Collaborate with stakeholders to ensure analytics-ready data delivery.
• Develop reusable data patterns and frameworks for scalable pipelines.
• Support QA, security, and governance across data products.

Skills

Data engineering

ETL/ELT

Azure

Python

SQL

NV1 clearance

Tools

Azure Data Factory

Databricks

SQL Server

Data Lake Storage

Power BI

Job description

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Job Description:

Australian Citizens residing in Australia only respond.

Job details

The EL1 Data Analyst (Labour Hire) provides specialist data analysis, data discovery and data delivery support for complex ICT programs, projects and digital services.

Working in multidisciplinary delivery teams, the role examines complex data from internal and external sources, defines how data should be interpreted and used, and translates business needs into clear data requirements, mappings, rules and analytical outputs.

The role works closely with business owners, data engineers, business analysts, architects, developers, testers and technical specialists across the end-to-end data lifecycle, from source discovery and profiling through to ingestion, validation, reconciliation, reporting and production support.

Key duties and responsibilities

• Lead data discovery and profiling across complex internal and external datasets to understand their structure, content, quality, lineage, relationships, constraints, sensitivity and fitness for purpose.
• Work with business and technical stakeholders to identify required data, clarify its business meaning, define the intended use and translate business outcomes into detailed data requirements and agreed data contracts.
• Develop and maintain source-to-target mappings, data dictionaries, field definitions, data contracts, transformation rules, join logic, filtering rules, matching logic and other implementation-ready data specifications.
• Analyse data using SQL and relevant analytics tools to identify duplicates, outliers, nulls, invalid values, inconsistent formats, referential issues and other data quality concerns.
• Define practical options for cleansing, standardising, transforming, matching, de-duplicating and reconciling data, including exception handling, rejected records, historical data, initial loads, incremental loads and refresh processes.
• Collaborate with data engineers and developers to translate approved mappings, data contracts and business rules into implementable ingestion, integration, migration and transformation logic, while maintaining clear end-to-end traceability.
• Support the design and delivery of data pipelines, bulk ingestion processes, system integrations, migrations and data refreshes across cloud and on-premises environments by clarifying requirements, resolving data questions and reviewing technical outcomes.
• Develop or prepare reusable datasets, SQL queries, analytical code, scripts, notebooks and supporting artefacts that enable profiling, transformation, reconciliation, testing and controlled implementation.
• Validate source and target data against approved mappings and data contracts, reconcile counts and key measures, investigate failed or incomplete loads, and support resolution of defects, exceptions and production data issues.
• Work with testers and business representatives to develop test scenarios, expected results and traceability from approved data requirements and mapping rules.
• Produce clear analysis, dashboards, reports, visualisations and written advice for both technical and non-technical audiences where required by the program or project.
• Identify and communicate data risks, assumptions, dependencies, limitations and gaps early, and provide evidence-based options and recommendations to delivery teams and senior stakeholders.
• Apply relevant data governance, privacy, security, records management and information handling requirements throughout analytical and delivery activities.
• Contribute to continuous improvement of data standards, documentation, reusable methods, quality controls and ways of working across data and digital delivery teams.

(NOTE: the key responsibilities of the role are based on current priorities and may change over time)

Required Skills:

Test Scenarios Records Management Reports Production Support Analysts Data Data Governance Cloud Support Options Data Quality Architects Pipelines Analysis Validation Developers Continuous Improvement Specifications Analytics Integration Records Security Data Analysis Testing Documentation Design Business SQL Management

About the Client

Our client is a Federal Government organisation delivering nationally significant scientific data, digital infrastructure and earth observation capabilities. Their work supports government, academia and industry through access to satellite imagery, spatial data and digital tools that help identify and understand physical changes across Australia and the Indo-Pacific.

They are seeking an experienced Lead Data Engineer to join a specialist Data Operations team supporting the maintenance and delivery of scientific products and infrastructure capabilities.

About the Role

As the Lead Data Engineer, you will work across data management, IT systems and earth observation product support, providing both hands‑on engineering expertise and technical leadership.

The position has a strong focus on cloud‑based data engineering, orchestration, containerisation and Python development, while ensuring security is embedded throughout solutions and delivery pipelines.

Key responsibilities will include:

• Designing, developing, validating, maintaining and optimising machine learning workflows through orchestration, testing and documentation.
• Supporting the development and maintenance of data sourcing, ingestion and transformation pipelines.
• Contributing to the development, testing and maintenance of the Open Data Cube code base.
• Implementing, maintaining and improving automated testing and deployment pipelines within AWS environments.
• Providing technical leadership across software development and championing secure, high‑quality engineering practices, tools and standards.
• Supporting knowledge transfer and upskilling of Earth Observation Scientists and providing guidance on improvements to existing algorithms.
• Embedding security tools and practices within systems and CI/CD pipelines.
• Helping ensure services and components remain available and high performing.
• Working collaboratively across technical teams while contributing to a strong, collaborative engineering culture.

The technical environment may include AWS, Kubernetes, Terraform, Python, PostgreSQL, Flyte, Airflow, Argo, data processing pipelines, big data technologies and GIS software. Candidates are not expected to have experience across every technology listed.

The Successful Candidate

To succeed in this position, you will be an accomplished Data Engineer who can combine strong hands‑on engineering capability with technical leadership and stakeholder engagement.

You will bring:

• Demonstrated experience working with large geospatial datasets in a cloud environment.
• Comprehensive understanding of protocols associated with data access and editing.
• Strong experience designing, developing and maintaining modern data ingestion, transformation and processing pipelines.
• Expertise in data engineering orchestration, containerisation and Python.
• Experience providing strategic advice and guidance on the effective use and reuse of data processes, systems and tools.
• The ability to provide technical leadership across software development and drive the adoption of effective engineering practices, tools and standards.
• A strong understanding of delivering secure, reliable and high‑quality technical solutions.
• Excellent stakeholder engagement skills, with the ability to communicate complex technical concepts effectively to both technical and non‑technical audiences.
• Strong relationship‑building and collaborative skills, with the ability to contribute positively to an inclusive, high‑performing team environment.

Location: The role is based in Canberra ACT.
Contract terms: 12 months from commencement date, plus 1x 6 month extension.
Security Requirements: Candidates must hold a minimum Baseline security clearance.
Citizenship: Applicants must be Australian citizens and hold, or be eligible and willing to obtain, Negative Vetting Level 1 (NV1) clearance.

What You’ll Need to Succeed

• Recent demonstrated experience as a Data Engineer, across the federal government landscape, supported by relevant qualifications or training.
• Strong experience developing ETL and ELT processes for large or complex data movement and transformation, ideally in cloud environments.
• Hands‑on capability across Azure Data Factory, Databricks, SQL Server, Data Lake Storage and related analytics services.
• Experience preparing data for query performance, advanced analytics and AI use cases using formats such as Parquet or Delta.
• Strong leadership, stakeholder engagement, negotiation and written and verbal communication skills.
• The ability to take ownership, work productively and collaborate within an Agile, multidisciplinary environment.
• A current NV1 security clearance, or the willingness and eligibility to obtain one, with commencement subject to obtaining Baseline clearance.

What You’ll Get in Return

This is an excellent opportunity to lead meaningful data engineering work within a high‑profile Federal Government environment. The role is based in Canberra and offers an initial up to 12‑month contract, with two possible up to 12‑month extensions, providing long‑term project potential and exposure to modern Azure, Databricks, lakehouse and analytics technologies.

What You Need to Do Now

Applications open until 8am 13 November 2026. Contact Damien on for any further information.

Australian Citizens residing in Australia only respond. must have baseline clearance.

Required Skills: Collaboration Creativity Strategic Thinking Azure Deep Learning Ethics Cloud Computing React Scalability Microsoft Azure Programming Languages Reliability Storage R Machine Learning Analytics TypeScript Programming Security Research Testing Planning Design JavaScript Python Business

Location: Canberra CBD, ACT | Hybrid

Engagement: 12‑month contract, with two possible 12‑month extensions

About INGRITY:

INGRITY is a specialist Data, Digital, Cloud & AI consultancy, helping organisations turn complex data into practical business outcomes.

We’re looking for an experienced Lead Data Engineer to support a federal government department’s enterprise analytics and technology services team.

About the Role:

You’ll lead the design, build and testing of data ingestion, transformation and visualisation solutions across Azure and Databricks, preparing data to support decision‑making across the department.

What You’ll Do:

• Design, build, test and maintain data ingestion and transformation solutions that meet current and emerging needs.
• Develop reusable, automated ingestion and transformation patterns and frameworks.
• Prepare data for analytics, visualisation and AI use cases, with a focus on quality and query performance.
• Support data engineers across delivery teams through quality reviews and constructive feedback.
• Collaborate with project teams to deliver outcomes aligned with departmental and program priorities.
• Participate in agile delivery, including in‑person attendance at quarterly agile ceremonies and key team events.

What We’re Looking For:

• Data engineering experience: At least five years’ experience as a data engineer, supported by relevant qualifications or training.
• ETL and ELT delivery: Strong experience developing solutions for large or complex data movement, transformation and visualisation, particularly in cloud environments.
• Performance optimisation: Experience preparing data for efficient querying in cloud compute engines, including Spark, graph databases and Azure SQL.
• Automated ingestion: Experience sourcing and ingesting data from Oracle, Ingres, Azure and SQL Server environments.
• Analytics‑ready data: Experience transforming data into Parquet and Delta formats for advanced analytics and AI use cases.
• Power BI: Ability to analyse complex datasets and design visualisations suited to the intended audience.
• Communication and collaboration: Strong written and verbal communication, relationship‑building and negotiation skills.

Nice to Have:

• Experience using Azure Data Factory and Databricks together.
• Knowledge of data lake and lakehouse architectures.
• Experience with ArcGIS Enterprise.

Why Join?

• Deliver data engineering solutions that support decision‑making across a federal government department.
• Work across Azure and Databricks within an established agile team.
• Combine hands‑on engineering with technical leadership and quality oversight.
• Secure a 12‑month engagement with the possibility of two further 12‑month extensions.

Citizenship and Security Clearance: Applicants must be Australian citizens and hold, or be eligible and willing to obtain, Negative Vetting Level 1 (NV1) clearance.