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About Us
Operating in nearly 40 countries across the world, our purpose is to be the best part of the journey. Whether our customers are flying abroad on holiday, heading off on a business trip or commuting to work by train, we aim to offer them food and drink experiences that meet their many different tastes and needs.

What You’ll Get from Us
Our Commitment to learning and development is our commitment to unlocking our people’s success. We strive to provide a wide range of resources that boost our people’s skills today, and help them fulfil their potential tomorrow. No matter where you join us, you’ll have all the tools you need to take charge of your development. Surrounded by like-minded colleagues and guided by industry experts, it’s your career, your way at SSP.

Data Engineer, Asia Pacific

About the Role

 

Data Engineer (Azure Databricks) | 1-Year Contract


We are looking for a hands-on, execution-driven Data Engineer to join our team on a contract basis. In this role, you will work directly alongside our Lead Data Engineer and Analytics Engineers to build and maintain scalable cloud data pipelines, establishing robust Bronze and Silver layers within our Medallion Architecture to support strategic BI initiatives (Power BI & Sigma). This position offers a balanced split between new pipeline engineering, quality assurance, operational troubleshooting, and ad-hoc data support.

Key Responsibilities & Work Allocation

Pipeline Engineering & QA (60%)

  • Design, build, and deploy ETL/ELT pipelines on Azure Databricks.
  • Construct and optimize Bronze (Raw Ingestion) and Silver (Cleaned & Conformed) data layers.
  • Conduct rigorous Data Quality QA, implementing automated testing frameworks to ensure data accuracy and consistency before handoff to Analytics Engineers.

Pipeline Debugging & Maintenance (30%)

  • Monitor, troubleshoot, and optimize existing Azure Databricks workflows and legacy data jobs.
  • Resolve pipeline failures, manage data schema drift, and optimize PySpark query performance to meet strict SLAs.

Ad-hoc Analysis & Stakeholder Support (10%)

  •  Conduct root-cause analysis on data discrepancies and support immediate business queries.
  • Collaborate with Analytics Engineers to ensure seamless downstream modeling (Gold layer / Data Marts) for Power BI and Sigma.

Technical Qualifications & Experience
Must-Have
•    2–4 years of hands-on Data Engineering experience in building and operating production-grade cloud data pipelines.
•    Hands-on proficiency with Azure Databricks, PySpark, and Spark SQL.
•    Demonstrated experience constructing Bronze and Silver layers using Medallion architectures.
•    Strong SQL skills (complex transformations, window functions, and performance tuning).
•    Solid understanding of data pipeline testing, QA methodologies, and automated data validation.
•    Familiarity with supporting BI tools such as Power BI or Sigma.
•    Experience with Git and standard version control/CI/CD practices.

Nice-to-Have
•    Experience working alongside Analytics Engineers using dbt (data build tool).
•    Exposure to cloud orchestration tools like Apache Airflow.
•    Exposure to core cloud data services across Azure, AWS, or GCP (e.g., ADLS Gen2, S3, or GCS).

Apply now »