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DATA ENGINEER (SSE / STAFF ENGINEER)

ALOIS UK

SydneyFull-timeMid LevelOn-site

Job Description

About Us


ALOIS Australia is a leading Talent and Technology Solutions company, focused on helping businesses across the country build stronger teams, smarter processes, and sustainable growth.


About Us


ALOIS Australia is a leading Talent and Technology Solutions company, focused on helping businesses across the country build stronger teams, smarter processes, and sustainable growth. We work with organisations in diverse industries to deliver integrated workforce and technology solutions, from innovative hiring strategies to end-to-end digital transformation. Our approach combines data, insight, and human expertise to help clients solve complex workforce challenges with clarity and confidence.

Through our deep industry experience and commitment to excellence, we provide scalable, high-performance solutions that deliver measurable impact. Whether it’s onshore project delivery, workforce optimisation, or specialised technology services, ALOIS Australia ensures results that truly make a difference. From Sydney to Perth and everywhere in between, we’re driven by one purpose: to empower Australian businesses and professionals to thrive in a rapidly changing world of work.

At ALOIS Australia, every challenge is an opportunity to innovate, and every partnership is built on trust, transparency, and long-term success.


Job Title – Data Engineer (SSE / Staff Engineer)


Job Location – Sydney


Employment Type – Contract/FTC


Role Overview


What role you will play in Team:


We are seeking a highly skilled Data Engineer (SSE / Staff Engineer) to design, build, and maintain scalable data platforms and pipelines on AWS. The ideal candidate will have strong expertise in Python, SQL, cloud-native data technologies, and modern data engineering practices.


Key Responsibilities



  • Design and develop scalable data pipelines for ingestion, transformation, and processing of large-scale data.

  • Build and maintain data solutions using AWS services such as Glue, Redshift, Athena, Step Functions, and related cloud-native services.

  • Implement streaming and batch data processing solutions using technologies such as Kafka and Flink.

  • Develop RESTful APIs and automation frameworks to support data services.

  • Ensure data quality, governance, security, and compliance requirements are met.

  • Create and maintain semantic and physical data models.

  • Collaborate with product owners, architects, business stakeholders, and cross-functional squads.

  • Implement CI/CD pipelines and DevOps best practices using Jenkins, Git, Docker, and Kubernetes.

  • Monitor, troubleshoot, and optimize data platform performance and reliability.

  • Contribute to architecture decisions and mentor junior engineers.


Required Qualifications



  • Strong hands-on experience with Python and SQL.

  • Experience with AWS data services including Glue, Redshift, Athena, and Step Functions.

  • Knowledge of Kafka, Flink, and modern Big Data technologies.

  • Experience designing data pipelines and ETL/ELT solutions.

  • Understanding of data governance and data modeling principles.

  • Hands-on experience with CI/CD, Docker, Kubernetes, IAM, and Vault.

  • Strong problem-solving and stakeholder management skills.

  • Experience working in Agile delivery environments.


Preferred Qualifications



  • Experience with large-scale cloud data platforms.

  • Knowledge of data lakehouse architectures and Apache Iceberg.

  • Experience with streaming analytics and event-driven architectures.

  • Prior experience in financial services or regulated industries.


Core Skills


Languages



  • Python

  • SQL


Data Technologies



  • AWS Glue

  • Redshift

  • Athena

  • Iceberg

  • Flink

  • Kafka

  • Understanding of Big Data technologies


Cloud / Hosting



  • AWS

  • Understanding of network design

  • AWS native services such as Step Functions


Data Engineering



  • Data pipelines

  • Airflow

  • Data ingestion

  • Data transformation

  • Data governance

  • Semantic and physical data modeling


APIs & Microservices



  • RESTful services

  • Automation scripts


DevOps



  • CI/CD (Jenkins, Git)

  • Docker

  • Kubernetes

  • IAM

  • Vault

  • Operations mindset


Security & Compliance



  • Data governance

  • Risk management


Agile Delivery



  • Collaboration with squads and stakeholders


Stay Connected With Us


Learn more about ALOIS in Australia, visit our webpage ALOIS Australia


Follow us on LinkedIn and Instagram


EEO Statement


ALOIS Australia is committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all qualified applicants and do not discriminate on the basis of race, colour, religion, sex, age, national origin, disability, or any other characteristic protected under applicable laws. We value diversity and believe it strengthens our people, our culture, and the outcomes we deliver.

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