An international financial technology operation in Estonia is looking for a skilled Financial Data Engineer to strengthen its real-time market-data and analytics infrastructure. The role focuses on transforming complex financial feeds into reliable, usable datasets for trading, research, risk, and business applications.

You will work across the complete market-data lifecycle, from ingestion and validation to processing, storage, and distribution. The successful candidate will have a strong engineering mindset and understand that financial data requires exceptional attention to accuracy, timing, consistency, and traceability.

Responsibilities

• Develop and maintain production-grade pipelines for financial and market data.
• Integrate external market-data feeds through APIs, streaming protocols, and vendor interfaces.
• Process real-time price, trade, order-book, volume, and reference-data streams.
• Design data transformations that standardise information from multiple sources.
• Implement validation rules to detect inaccurate, incomplete, duplicated, or delayed market data.
• Monitor data latency and investigate issues affecting real-time distribution.
• Build systems for storing and retrieving large volumes of historical market information.
• Support data availability for quantitative research, algorithmic trading, risk analysis, and reporting.
• Develop automated processes for data reconciliation and quality control.
• Work with researchers and analysts to understand dataset requirements and improve data accessibility.
• Collaborate with software engineers on APIs and services that expose market data to internal applications.
• Improve pipeline performance, reliability, scalability, and operational resilience.
• Develop monitoring dashboards and alerting mechanisms for critical data infrastructure.
• Maintain clear documentation for data sources, transformations, schemas, and operational processes.
• Participate in the design of new data architectures as market-data requirements expand.

What We Are Looking For

• Experience in data engineering, financial technology, market-data systems, or a comparable technical environment.
• Strong Python and SQL capabilities.
• Experience working with streaming data, APIs, ETL/ELT pipelines, and distributed data systems.
• Good understanding of financial-market data structures and terminology.
• Experience with technologies such as Kafka, Spark, Airflow, PostgreSQL, ClickHouse, or equivalent platforms is advantageous.
• Familiarity with AWS, Azure, GCP, or another cloud environment is beneficial.
• Understanding of data modelling, schema design, data lineage, and quality controls.
• Strong analytical and troubleshooting skills.
• Ability to work with high-volume and time-sensitive datasets.
• Excellent attention to detail and commitment to data integrity.
• Strong communication skills and ability to collaborate across technical and financial teams.

Ideal Candidate

The ideal candidate is technically capable, methodical, and highly attentive to data quality. You should be comfortable working with large and constantly changing datasets while understanding the importance of low latency and reliable information in financial markets.

You should also be able to investigate a data problem from multiple angles—from the original external feed through transformation and storage to the final application consuming the information.

Opportunity

This position offers an opportunity to work at the intersection of data engineering, financial markets, cloud technology, and real-time analytics. It is well suited to an engineer seeking deeper specialisation in financial data and the infrastructure behind modern electronic markets.

Are you interested in this position?

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