Data Engineer

The client is an established FinTech software provider with more than 25 years of experience delivering banking technology to regulated financial institutions. Its product ecosystem covers core banking, digital onboarding, multi-currency accounts, payments, compliance, and AML. The company’s platforms support international banking and payment operations, including connectivity to infrastructure such as SEPA, Faster Payments, Bacs, T2 and CENTROlink. The business serves international clients and forms part of a larger global technology group.

As a Data Engineer, you will build and improve the data infrastructure behind account, transaction, payment and customer data flows. Your work will help teams access reliable data for operational processes, reconciliation, reporting, compliance, risk, and product development.

This is a hands-on engineering role with scope to influence data architecture, standards, and platform priorities. You will work closely with product, engineering, data, compliance, finance, and operations specialists to turn complex financial data requirements into dependable production solutions.

You will take ownership of data platform initiatives, from architecture and technical design to production delivery, supporting scalable batch and real-time processing. This is a full-time, fully onsite position in Vilnius, Lithuania.

• Design, build, and operate scalable, high-volume batch, streaming, and event-driven data pipelines for banking, payment, customer, and transactional data;
• Integrate data from core banking applications, payment infrastructure, internal services, and external providers;
• Create reliable data models and datasets for operational reporting, reconciliation, compliance, risk, finance, and analytics;
• Support analytics and machine learning teams by delivering reliable, well-structured data products and feature stores;
• Standardise ETL/ELT pipeline development using Airflow, dbt, or equivalent technologies, with automated testing, deployment, monitoring, and documentation;
• Introduce automated controls for data quality, lineage, consistency, and observability;
• Design, maintain, and optimise cloud data warehouse and lakehouse solutions for performance, reliability, scalability, and cost efficiency;
• Work with product and business teams to translate operational requirements into maintainable data solutions;
• Apply security, privacy, governance, and auditability principles throughout the data lifecycle;
• Own the data engineering roadmap and establish engineering standards, code review practices, architecture decisions, and cross-team knowledge sharing.

• Proven hands-on experience designing, delivering, and operating production-grade data platforms and high-volume pipelines, with end-to-end ownership of delivery;
• Strong Python and SQL skills for data processing, automation, transformation, and integration;
• Hands-on experience with distributed data processing frameworks such as Apache Spark, Databricks, or comparable technologies;
• Experience with pipeline orchestration tools such as Airflow and transformation frameworks such as dbt, or equivalent technologies;
• Hands-on experience building and operating streaming and event-driven data pipelines using Kafka or equivalent technologies;
• Practical experience with ETL/ELT, data modelling, cloud data warehouses such as Snowflake, Redshift or BigQuery, and data lake/lakehouse architectures;
• Strong hands-on experience with AWS, Azure, or GCP, including deployment and operation of production data infrastructure;
• Ability to design reliable integrations between databases, APIs, applications, and external systems;
• Hands-on experience with CI/CD, automated testing, data quality, monitoring, and observability, with familiarity with infrastructure as code, containerisation (Docker), and orchestration (Kubernetes);
• Professional English and the ability to work effectively with technical and business stakeholders.
• Knowledge of banking, payments, transaction processing, reconciliation, or regulated financial services;
• Familiarity with SEPA, SWIFT, ISO 20022, CENTROlink, Open Banking, or card payment ecosystems;
• Exposure to data products supporting AML, regulatory reporting, risk, finance, analytics, or machine learning;
• Exposure to MLOps, feature stores, LLM/RAG pipelines, or vector search technologies.

✨ The Employer Offers

• Meaningful ownership of data solutions supporting core banking and payment infrastructure;
• The opportunity to influence data architecture, engineering standards, and platform development;
• Work with complex transactional data used in regulated financial operations;
• Exposure to banking, payments, reconciliation, compliance, and financial reporting use cases;
• International scope across clients, partners, products, and implementation projects;
• Close collaboration with experienced product, engineering, compliance, finance, and operations specialists;
• The stability and reach of an established financial technology provider within an international group.

If you enjoy solving complex data problems and want your work to support financial systems used in everyday banking and payments, apply and help build a dependable data foundation for the client’s next stage of development.