AVP, Big Data Engineer, Data Technology, Technology and Operations
Job details
Business Function Group Technology and Operations (T&O) enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group T&O, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels. We are looking for a Big Data Engineer that will work on developing frameworks using Spark and Spring Boot microservices to create jobs for collecting, storing, processing, and analysing of huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them. You will also be responsible for integrating them with the architecture used across the company. Responsibilities
- Implementing Big Data tools and frameworks required to provide requested capabilities.
- Work with stakeholders including the Product owner, Data and Design teams to assist with
- data-related technical issues and support their data infrastructure needs.
- Support customers implementing ETL process
- Monitoring performance and advising any necessary infrastructure changes
- Bachelor's degree in Computer Science or a related field. At least 7 years of IT experience of which at least 5 years' experience in similar role, ideally in a Big Data tools.
- Proficient understanding of distributed computing principles
- Strong experience of Hadoop, Spark, Iceberg and Spring Boot
- Experience with building stream-processing systems, using solutions such as Spark-Streaming
- Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
- Experience with integration of data from multiple data sources
- Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
- Knowledge of various ETL techniques and frameworks
- Experience with various messaging systems, such as Kafka or RabbitMQ
- Knowlege with Big Data ML toolkits, such as Mahout, SparkML, or H2O
- Good understanding of Lambda Architecture, along with its advantages and drawbacks
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