Data Engineer

With 100+ AI and custom software experts across engineering hubs in Lithuania and Poland, we embed ourselves directly into client operations — delivering custom software, automation, and AI where they drive the most value.</p><p>We are seeking for a Senior Data Engineer for our client from the banking sector.</p><h3>Job description:</h3><ul><li>Design, implement, and continuously improve systems for data ingestion, processing, storage, and sharing</li><li>Build and optimize data architectures for performance, scalability, and reliability</li><li>Develop and maintain ETL/ELT pipelines using modern tools and frameworks</li><li>Ensure seamless integration and synchronization across systems</li><li>Uphold high standards of data quality, security, availability, and performance</li><li>Collaborate with analysts, software engineers, and business stakeholders to understand data needs and deliver solutions</li><li>Perform code reviews, troubleshoot software, and fix defects</li><li>Implement monitoring and alerting for data workflows</li><li>Gain expertise in a variety of banking processes and products</li></ul><h3>Requirements</h3><ul><li>3-5+ experience in a Data engineer position or a similar position, experience in financial industry considered as a Pluss.</li><li>Proven experience with SQL and Python; Other ETL engines are a plus</li><li>Experience with both SQL and NoSQL databases</li><li>Hands-on experience with the cloud platforms (AWS or Azure or GCP)</li><li>Experience with container orchestration tools (Kubernetes, Docker)</li><li>Understanding of streaming data pipelines and platforms (Kafka, Spark, Flink)</li><li>Familiarity with data pipeline tools like Airflow or dbt</li><li>Experience with data warehousing solutions (Snowflake, BigQuery, Redshift)</li><li>Knowledge of solution integrations (real-time, message-based, event-driven)</li><li>Exposure to test automation and DevOps practices, including infrastructure as code and security best practices</li><li>Experience within the risk or finance business domain is a strong advantage</li><li>Ability to take ownership and drive initiatives independently</li><li>Fluent English</li></ul><h3>Benefits</h3><ul><li>Diverse and technically challenging projects.</li><li>Flexible working hours and a hybrid or remote workplace model.</li><li>Flexible schedule and an Agile/SCRUM environment.</li><li>Technical equipment that you can choose.</li></ul><p>Originally posted on <a href="https://himalayas.app">Himalayas</a></p>

Softeta is a software engineering partner for finance, energy, industrial, and other high-stakes sectors. We specialize in building and modernizing backend-heavy, integration-critical systems where speed, accuracy, and reliability are non-negotiable. With 100+ AI and custom software experts across engineering hubs in Lithuania and Poland, we embed ourselves directly into client operations — delivering custom software, automation, and AI where they drive the most value.

We are seeking for a Senior Data Engineer for our client from the banking sector.

Job description:

• Design, implement, and continuously improve systems for data ingestion, processing, storage, and sharing
• Build and optimize data architectures for performance, scalability, and reliability
• Develop and maintain ETL/ELT pipelines using modern tools and frameworks
• Ensure seamless integration and synchronization across systems
• Uphold high standards of data quality, security, availability, and performance
• Collaborate with analysts, software engineers, and business stakeholders to understand data needs and deliver solutions
• Perform code reviews, troubleshoot software, and fix defects
• Implement monitoring and alerting for data workflows
• Gain expertise in a variety of banking processes and products

Requirements

• 3-5+ experience in a Data engineer position or a similar position, experience in financial industry considered as a Pluss.
• Proven experience with SQL and Python; Other ETL engines are a plus
• Experience with both SQL and NoSQL databases
• Hands-on experience with the cloud platforms (AWS or Azure or GCP)
• Experience with container orchestration tools (Kubernetes, Docker)
• Understanding of streaming data pipelines and platforms (Kafka, Spark, Flink)
• Familiarity with data pipeline tools like Airflow or dbt
• Experience with data warehousing solutions (Snowflake, BigQuery, Redshift)
• Knowledge of solution integrations (real-time, message-based, event-driven)
• Exposure to test automation and DevOps practices, including infrastructure as code and security best practices
• Experience within the risk or finance business domain is a strong advantage
• Ability to take ownership and drive initiatives independently
• Fluent English

Benefits

• Diverse and technically challenging projects.
• Flexible working hours and a hybrid or remote workplace model.
• Flexible schedule and an Agile/SCRUM environment.
• Technical equipment that you can choose.

Originally posted on Himalayas