Lead Data Analyst (EL1)

WattleCore Technologies Pty Ltd; Canberra; Hybrid; AUD 110,000 - 140,000; Full time

Job summary

WattleCore Technologies Pty Ltd in Canberra seeks an EL1 Data Analyst to provide specialist data analysis, discovery and data delivery support for complex ICT programs. You will examine data from multiple sources, translate business needs into clear data requirements, mappings and rules, and deliver analytical outputs for stakeholders across the end-to-end data lifecycle.

The role will primarily use SAS, SAS Studio and Snowflake with a focus on SQL-based analysis, data cleansing and

Qualifications

• Extensive experience undertaking data discovery, profiling and analysis across complex datasets in ICT/digital delivery.
• Strong practical experience using SQL and contemporary data analysis tools to interrogate complex data and develop analytical code.
• Developer experience with data mappings, data contracts, data definitions and transformation rules.

Responsibilities

• Lead data discovery and profiling across complex datasets to understand structure, quality and lineage.
• Translate business needs into data requirements, mappings and data contracts.
• Develop and maintain source-to-target mappings, dictionaries and transformation rules.
• Analyse data using SQL to identify quality issues and describe data quality concerns.
• Collaborate with data engineers to implement ingestion, integration and transformation logic.
• Prepare datasets, queries, scripts and artefacts for profiling, testing and deployment.
• Validate data against mappings and contracts, reconcile counts and investigate defects.
• Produce dashboards, reports and visualisations for technical and non-technical audiences.

Skills

Data discovery

Data analysis

SQL

Stakeholder engagement

EL1 level autonomy

Tools

SQL

SAS Studio

Snowflake

Job description

Canberra, Australian Capital Territory 2600, Australia

Full-time Contract Associate

Description

Employment typeContract

CategoryBusiness Analysis

Security clearanceNV1

LocationCanberra, Sydney, Melbourne, Brisbane, Adelaide, Hobart, Darwin, ACT

About the role

The NDIA's title for this position is EL1 Data Analyst. It 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.

You will work 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.

The buyer has confirmed this is a new position, not a backfill, and that the role will primarily use SAS, SAS Studio and Snowflake, with a focus on SQL-based data analysis, mapping, transformation, validation and data quality. Snowflake is a key source platform for the data the role works with.

Estimated start 7 December 2026. 12-month initial contract with one 12-month extension option. 37.5 hours per week. Hybrid working is available subject to negotiation with the line manager, in line with current NDIA policy — a minimum of three days each week in the office, with flexible arrangements for the remaining two.

Applications must respond to each essential and desirable criterion below individually, in up to 3,000 characters each. The proposed rate should reflect the candidate's skills and experience against those criteria; candidates who do not demonstrate them will not be assessed.

You must be able to obtain a Negative Vetting Level 1 security clearance.

Australian citizenship is mandatory. The successful candidate must provide evidence of citizenship during the pre-engagement check.

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 its 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 and 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, maintaining end-to-end traceability.
• Support the design and delivery of data pipelines, bulk ingestion, system integrations, migrations and data refreshes across cloud and on-premises environments by clarifying requirements, resolving data questions and reviewing technical outcomes.
• Prepare reusable datasets, SQL queries, analytical code, scripts, notebooks and supporting artefacts for 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 help resolve 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 technical and non-technical audiences where the program or project requires it.
• Identify and communicate data risks, assumptions, dependencies, limitations and gaps early, with evidence-based options and recommendations for delivery teams and senior stakeholders.
• Apply data governance, privacy, security, records management and information handling requirements throughout analytical and delivery activities, and contribute to continuous improvement of data standards, documentation, reusable methods and quality controls.

Skills & experience

• Demonstrated extensive experience undertaking data discovery, profiling and analysis across complex datasets in an ICT, digital transformation or data delivery environment.
• Strong practical experience using SQL and contemporary data analysis tools to interrogate complex data, develop analytical code or scripts, identify quality issues and undertake detailed technical investigation.
• Demonstrated experience developing source-to-target mappings, data contracts, data definitions, transformation and business rules, join and matching logic, exception handling and other implementation-ready data specifications.
• Demonstrated experience across the end-to-end data lifecycle: discovery, lineage and traceability, ingestion or integration, migration, initial and incremental loads, validation, reconciliation, defect investigation and implementation support.
• Demonstrated ability to translate complex business and technical requirements into clear data artefacts and delivery specifications, communicating effectively with business stakeholders, engineers, architects, developers and testers.
• Strong analytical, problem-solving, documentation and stakeholder engagement skills, with the ability to work independently at EL1 level and collaboratively in multidisciplinary delivery teams.

Nice to have

• Experience with SAS Viya or SAS Studio, Snowflake, SQL, Python, Power BI, Talend, Azure data services or comparable data and analytics technologies.
• Experience supporting large-scale data migration, bulk ingestion, cloud data platforms, system integration, data refresh or digital transformation initiatives in a complex environment.
• Experience with data modelling, entity and relationship data, reference data, de-duplication, matching, lineage or reconciliation approaches.
• Knowledge of Australian Government data governance, privacy, security and information management requirements.