Data Engineer: Governance, Pipelines & Quality

Accenture PLC; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

Accenture PLC is seeking an experienced Data Engineer to create and provide access to high quality data solutions and pipelines. You will collaborate with colleagues to develop best practice data solutions, ensuring data integrity to enable data-driven decisions.

In a DevOps model, you will develop data pipelines using CI/CD techniques and work across complex data landscapes to drive reliability, scalability and insights for business outcomes.

Qualifications

• Experience delivering data solutions and pipelines in a modern data stack.
• Knowledge of data quality, governance and best practices.
• Ability to communicate complex data concepts to technical and non-technical stakeholders.

Responsibilities

• Evaluate complex business information to define problems and implement best practice solutions.
• Collaborate with Senior Data Engineers and Architects on data design and optimisation.
• Install, test and maintain data systems using diverse data sources and techniques.
• Source and analyse data sets from multiple sources to enable ingestion and preparation for modelling.
• Investigate data quality issues and drive improvements in reliability and speed.
• Prepare data for predictive modelling and ensure quality for cross-team use.
• Contribute to embedded firmware frameworks for service deployment on gateways.
• Support infrastructure and DevOps tooling for streaming software deployments.
• Present technical information to stakeholders to align scope and milestones.

Skills

Analytical Thinking

Attention to detail

SQL

Python

Spark

Kafka

Communication

Container Technologies

CI/CD

Data Wrangling

Data Visualization

ETL

Hadoop

Presentation

REST APIs

Job description

Accenture PLC is seeking an experienced Data Engineer to create and provide access to high quality data solutions and pipelines. You will collaborate with colleagues to develop best practice data solutions, ensuring data integrity to enable data-driven decisions.

In a DevOps model, you will develop data pipelines using CI/CD techniques and work across complex data landscapes to drive reliability, scalability and insights for business outcomes.