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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.DescriptionDesign, build, and improve data architectures with a focus on performance, scalability, and reliability.Develop and maintain ETL/ELT pipelines for data ingestion, transformation, storage, and sharing.Integrate data across systems and ensure consistent, reliable synchronization.Maintain high standards of data quality, security, and availability, supported by monitoring and alerting.Collaborate with analysts, software engineers, and business stakeholders to translate data needs into practical solutions.Review code, troubleshoot data workflows, resolve defects, and continuously improve engineering practices.Requirements5+ years of experience in data engineering or a similar role. Experience in financial services, particularly risk or finance, is a strong advantage.Strong SQL and Python skills. Familiarity with additional ETL tools is a plus.Hands-on experience with at least one cloud platform (AWS, Azure, or GCP).Data warehousing solutions such as BigQuery or Redshift.Experience with Docker and Kubernetes, alongside familiarity with DevOps practices, Terraform, test automation, infrastructure as code, and security best practices.Understanding of streaming data pipelines and technologies such as Kafka, Spark, or Flink.Familiarity with orchestration or transformation tools such as Airflow or dbt.Knowledge of system integration approaches, including real-time, message-based, and event-driven integrations.BenefitsDiverse 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.
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