We are looking for a Principal Data Engineer who will play a crucial role in delivering measurable business value through the strategic use of Data and Analytics across the organisation. This position requires a strong blend of technical depth, functional understanding, and leadership capability to drive complex, end-to-end data programmes.

The role spans consulting, architectural design, engineering oversight, and solution definition, ensuring that all data initiatives are aligned with organisational goals and delivered to a consistently high standard. The ideal candidate will bring extensive hands-on experience across data engineering, data and solution architecture, data integration, master data management, data quality, enterprise data warehousing, and analytics. They will be responsible for shaping the data strategy, providing technical authority, and leading programmes that maximise the organisation’s ability to leverage its data assets.

Key Responsibilities:

Define and Drive Data Strategy - Develop and evolve the enterprise data architecture and strategy, ensuring alignment with business priorities and long-term organisational objectives.
Lead End-to-End Data Programmes - Provide architectural and engineering leadership across complex data initiatives, from discovery and design through to delivery and optimisation.
Provide Technical Authority - Act as a senior technical leader and decision-maker across data architecture, engineering standards, tooling, and design patterns.
Architect and Build Scalable Data Solutions - Design and hands-on build robust, scalable, and secure data platforms and solutions that support analytics, reporting, operational use cases, and advanced analytics/AI.
Align Business and Technology - Work closely with business stakeholders, product owners, and delivery teams to translate business needs into effective data and analytics solutions.
Oversee and Contribute to Data Engineering Delivery - Guide and actively contribute to engineering teams to ensure solutions are implemented in line with architectural standards, best practices, and performance expectations.
Champion Data Governance and Quality - Promote strong practices in data governance, master data management, metadata management, and data quality across the organisation.
Drive Integration and Interoperability - Ensure seamless integration of data across systems and domains, enabling a connected and trusted data ecosystem.
Mentor and Lead - Coach architects, engineers, and analysts, raising overall data maturity and fostering a culture of technical excellence and continuous improvement.
Engage in Strategic Consulting - Provide thought leadership and advisory support to senior stakeholders on how to unlock business value through data and analytics.

Experience & Skills Required:

10+ years of hands-on experience in data engineering, data architecture, or enterprise data management roles, with a significant portion spent writing and delivering production-grade data pipelines and solutions.
Proven track record of leading large-scale, end-to-end data programmes in complex organisational environments.
Deep expertise in data architecture, solution architecture, and data platform design, backed by practical hands-on delivery.
Strong hands-on experience building and operating data integration solutions, including ETL/ELT pipelines, real-time streaming (e.g. Kafka, Spark Streaming), and API-based data exchange.
Proven hands-on proficiency with modern data engineering tools and frameworks such as dbt, Apache Spark, Airflow/Prefect, or equivalent orchestration and transformation technologies.
Solid background in Master Data Management (MDM), data quality, and data governance frameworks and tooling, with direct implementation experience.
Extensive hands-on experience designing and building enterprise data warehouses and modern analytics platforms (e.g. Snowflake, BigQuery, Databricks, Azure Synapse, Redshift).
Hands-on experience developing data solutions that support BI, reporting, advanced analytics, and data science use cases, including working knowledge of semantic layers and data modelling techniques (e.g. Kimball, Data Vault).
Strong hands-on experience with cloud data ecosystems (AWS, Azure, or GCP), including infrastructure-as-code, cloud-native data services, and DevOps/DataOps practices.
Ability to operate at both strategic and hands-on levels, from high-level architecture to writing and reviewing production code.
Excellent stakeholder management, communication, and consulting skills, with the ability to influence senior technical and non-technical audiences.
Experience working in large, complex, or regulated environments is highly desirable.

About INGRITY:

We are a fast-growing, progressive Sydney-based data & analytics company. We service many large corporates and SMBs in the financial services sector, to derive value from data. At Ingrity, we are committed to building a diverse and inclusive workforce to deliver value to customers. As a value-driven organisation, we nurture and support our people by having a laser-sharp focus on skill and talent development, collaboration, and flexibility.