Principal Financial Data Engineer

Turn Complex Financial Data Into Trusted Intelligence

An innovative fintech organization in Estonia is seeking a Principal Financial Data Engineer to design and lead data infrastructure supporting financial analytics, transaction intelligence, risk management, product optimization, and regulatory reporting.

This role is ideal for a senior data professional who understands both modern data engineering and the unique demands of financial information. You will help establish reliable data foundations capable of processing large volumes of transactional information while maintaining accuracy, traceability, governance, and security.

Key Responsibilities

• Architect scalable data platforms for transaction, customer, payment, account, and financial-product data.
• Develop robust batch and real-time data pipelines supporting mission-critical fintech applications.
• Design data models and processing frameworks for financial analytics and operational intelligence.
• Build streaming architectures capable of processing high-volume transaction events in near real time.
• Establish reliable data-quality, validation, lineage, and reconciliation mechanisms.
• Collaborate with data scientists and risk teams to prepare trusted datasets for predictive analytics and machine-learning applications.
• Design secure data-access frameworks while maintaining appropriate privacy and governance controls.
• Optimize data infrastructure for performance, scalability, cost efficiency, and reliability.
• Support financial reporting, operational dashboards, risk analysis, and regulatory data requirements.
• Establish engineering standards for data observability, testing, documentation, version control, and deployment.
• Mentor data engineers and contribute to the organization’s broader data-platform strategy.

What You Bring

• 7+ years of experience in data engineering, data architecture, analytics engineering, or a comparable technical discipline.
• Strong experience designing enterprise-grade data platforms and pipelines.
• Advanced Python and SQL skills.
• Practical experience with technologies such as Spark, Kafka, Airflow, dbt, or equivalent data-engineering platforms.
• Strong understanding of relational and analytical databases, data warehousing, and data-lake architectures.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of financial transactions, payments, banking data, risk analytics, or another data-intensive financial environment.
• Strong understanding of data governance, data quality, lineage, security, and access management.
• Ability to communicate complex technical concepts to both engineering and non-technical stakeholders.

Technical Environment

The technology landscape may include Python, SQL, Kafka, Spark, Airflow, dbt, PostgreSQL, Snowflake, cloud data platforms, object storage, Kubernetes, Terraform, and modern data-observability tooling.

Why This Opportunity

Financial technology increasingly depends on the quality and speed of its data infrastructure. In this role, your work will support decisions involving payments, risk, customer intelligence, financial performance, and product development while helping establish a highly reliable data ecosystem for future growth.

Ideal Candidate

You are a technically strong data professional who cares deeply about data correctness and engineering discipline. You understand that a financial data platform must be scalable without compromising accuracy, traceability, security, or business usability.

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!

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