Roles and Responsibilites:

Developing and optimising ETL (Extract, Transform, Load) processes to ingest and transform large volumes of data from multiple sources.
Must have experience in investment banking, payment and transaction banking domains.
Developing and deploying data processing applications using Big Data frameworks such as Hadoop, Spark, Kafka, or similar technologies.
Proficiency in programming languages and scripting (e.g., Java, Scala, Python, SQL) for data processing and analysis.
Experience with cloud platforms and services for Big Data (e.g., AWS, Azure, Google Cloud)

Requirements:

Primary Skills:

Designing, building, and maintaining systems that handle large volumes of data, enabling businesses to extract valuable insights and make data-driven decisions.
Creating scalable and efficient data pipelines, implementing data models, and integrating various data sources.
Developing and deploying data processing applications using Big Data frameworks such as Hadoop, Spark, Kafka
Write efficient and optimised code in programming languages like Java, Scala, Python to manipulate and analyse data
Creating scalable and efficient data pipelines, implementing data models, and integrating diverse data sources to enable businesses to extract valuable insights

Secondary Skills:

Designing, developing, and implementing scalable and efficient data processing pipelines using Big Data technologies.
Implementing a Kafka-based pipeline to feed event-driven data into a dynamic pricing model, enabling real-time pricing adjustments based on market conditions and customer
Conduct testing and validation of data pipelines and analytical solutions to ensure accuracy, reliability, and performance.
Strong experience in Spring Boot and microservices architecture.
Strong experience in distributed computing principles and Big Data ecosystem components (e.g., Hadoop, Spark, Hive, HBase).

Big Data Developer

Job Description