Senior Data Engineer (Kafka / Spark)

Quick Facts

• Role: Senior Data Engineer (Kafka / Spark)

• Focus: Banking sector data platform development using Kafka, Spark, and lakehouse architecture

• Collaboration length: Long-term; projects typically ~1 year

Description

You will design and build data pipelines and integrations, maintaining streaming solutions based on Kafka (Streams, Connect, ksqlDB) or Spark. The work includes defining data schemas and transformations, monitoring and optimizing performance, troubleshooting technical issues, and ensuring security of processed data. You will also create technical documentation and perform code reviews.

Responsibilities

• Design and develop data flows and integrations

• Build and maintain Kafka-based solutions (Streams, Connect, ksqlDB) or Spark

• Define data schemas and perform data transformations

• Monitor and optimize system performance

• Diagnose and resolve technical issues

• Ensure security for processed data

• Create technical documentation

• Conduct code reviews

Requirements

• Minimum 3 years of experience as a Data Engineer or Backend Developer in data processing

• Practical knowledge of Apache Kafka or Apache Spark

• Ability to program in Java (Spring Boot) or Python

• Experience with MongoDB or another NoSQL database

• Knowledge of CI/CD processes and DevOps practices

• Experience with monitoring tools (Prometheus, Grafana, OpenTelemetry)

Nice to have

• Knowledge of Apache Iceberg or Delta Lake

• Experience with Kafka security mechanisms (TLS, SASL, ACL)

• Practical knowledge of AWS

• Experience with Kubernetes and Terraform

• Prior experience with data warehouses in the financial industry

Process

• Short process: initial call, technical substantive interview, final decision