Job Description

About this job At JUMO, we’ve built a smart financial services platform to make finance accessible to everyone. Our Data engineering team ensures that our intelligent banking platform is able to acquire data from millions of users across globally distributed sources, such as GSM. Beyond ingress, the data is processed and stored in the cloud to support event-driven analytics and machine learning pipelines. As a JUMO Data Engineer, you will design, build and maintain scalable data architectures. You will monitor their performance, perform root cause analysis and provide solutions to any issues that might arise. You will work with large, complex data sets, which means experience working with Big Data is essential. On a typical day, we use Spark, Kafka, Python, SQL, Airflow and AWS technologies, such as Redshift. We work with Docker and Kubernetes for automating deployment, scaling, and management of containerized applications.

Responsibilities

You will:

Be responsible for creating robust, mission critical batch and streaming data processing capabilities

Design, implement, and maintain the data pipelines that constitute JUMO's data platform, enabling effective use of data across the organisation

Provide feedback on team members' output, encouraging skills development within the team

Work closely with Portfolio Managers and Decision Scientists to understand the real world problems we’re trying to solve

Mentor juniors with technical leadership

Be supported by senior leaders as you drive your own development

You will need:

BSc. in Computer Science, Electrical Engineering or equivalent tertiary degree

Real-world understanding & experience of data pipeline design and development, as well as data processing and storage (i.e. experience in designing systems to process and curate large data sets)

Experience in streaming technologies, specifically Spark and Kafka

Experience with cloud technologies, AWS preferred

Solid, proven experience working with big-data technologies such as Apache Spark, Flink, Hadoop, Kafka or Kinesis, DynamoDB

Command of productionising and monitoring of data pipeline workflows, and working knowledge of the Data Product Lifecycle

Experience in application design and development with at least one of the following languages: Python (preferred), Kotlin

RDBMS experience in any relevant technology such as MySQL, PostgreSQL, Redshift and SQL Server. This includes experience with relational database administration, technical architectures and infrastructure components

Understanding of CI/CD practices

Productive within a Linux command line environment

Proven ability to contribute software as part of a team. We are looking for someone that can effectively communicate technical concepts, and apply critical thinking under pressure

Bonus if you have:

Experience working with messaging systems (RabbitMQ, Redis, SNS)

Experience working with data pipeline orchestration (Airflow, Nifi, Dagster )

Experience working with production BI environments and tools (Tableau, Superset, Looker)

Data Engineer

Job Description

Stop applying into silence.

Responsibilities

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