Data Engineer - Palantir at Equans
Silverwater, New South Wales, Australia -
Full Time


Start Date

Immediate

Expiry Date

05 Dec, 25

Salary

0.0

Posted On

06 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Hadoop, Azure, Computer Science, Data Solutions, Apache Spark, Sql, Data Integration, Aws, Amazon Redshift, Data Services, Decision Making, Data Infrastructure, Google Cloud, Python, Scalable Architecture, Palantir

Industry

Information Technology/IT

Description

WE ARE SEEKING A HIGHLY SKILLED DATA ENGINEER WITH PALANTIR EXPERTISE TO JOIN OUR IT TEAM.

In this role, you will be responsible for designing, building, and maintaining the data infrastructure that enables the organisation to unlock insights, support analytics initiatives, and drive strategic decision-making.
A key component of this position is working with Palantir Foundry, ensuring seamless data integration and scalable architecture across the organisation.

ABOUT US

Equans Australia and New Zealand delivers multi-disciplinary technical solutions and facility management services with the aim to provide superior value to all stakeholders using a using an integrated facilities and project management approach. Find out more about Equans ANZ by visiting equans.com.au.

Responsibilities
  • Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines to process large-scale datasets from diverse sources, ensuring data quality and reliability.
  • Data Architecture & Modelling: Develop and implement data architecture and modelling strategies that support real-time and batch data processing with a focus on performance and scalability.
  • Data Integration: Integrate, transform, and enrich data from a variety of internal and external sources to support both operational and analytical use cases.
  • Optimisation & Performance Tuning: Analyse and enhance data ingestion, processing, and storage performance; optimise ETL/ELT workflows for efficiency.
  • Collaboration: Work closely with cross-functional stakeholders to understand data needs, deliver solutions, and provide mentorship and technical guidance to junior team members.
  • Data Governance: Uphold and implement data governance standards, ensuring compliance with data security, privacy, and regulatory requirements.
  • Documentation & Reporting: Maintain thorough documentation of data engineering processes and provide regular insights on system performance and data usage.
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