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We are seeking a GCP Data Engineer who will design, build, and operationalise cloud‑based data processing systems within the Software Engineering – BIBDA function. The individual will work extensively with Google Cloud Platform (GCP) services, Spark frameworks, and cloud‑native tooling to deliver reliable, efficient, and high‑quality data pipelines. This role is suitable for individuals with demonstrated experience in BigQuery, Data Fusion, Dataproc, and programming languages such as Python or Java.
Job Responsibility:
Build and operationalise data processing systems based on low‑level design requirements
Apply strong working knowledge of the Spark framework and hands‑on experience with Dataproc
Use GCP Data Fusion, BigQuery, Airflow, and related tools to support optimised and scalable development approaches
Apply cloud‑based data pipeline patterns and propose innovative solutions to navigate platform constraints
Design, test, and maintain data pipelines aligned with data modelling, data warehousing, and industry‑standard data manipulation techniques
Design, develop, and maintain programmes written in Python, Spark, Scala, Java, or related technologies
Contribute to organisational improvements through process adoption, resource optimisation, and the use of tools that enhance productivity and quality
Recommend approaches to improve data reliability, operational efficiency, and overall solution quality
Requirements:
Experienced in GCP tools including BigQuery, Data Fusion, Dataproc, Cloud Composer, Workflows, and Cloud Scheduler
Skilled in programming languages such as Python, Spark, PySpark, or Java
Knowledgeable in Apache Airflow, GCP Dataproc clusters, and Dataflow
Possess 2–4 years of overall experience, with at least 2–3 years working on cloud platforms such as GCP, AWS, or Azure
Preferably certified as a Google Cloud Professional Data Engineer
Hold a technical qualification such as B.E./B.Tech, BCA/MCA, or BSc/MSc in Computer Science