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Senior Data Engineer

Astra Tech Tbilisi, Georgia

Public Relations and Communications Services · 11-50 employees

4 d ago
data-engineer Senior (5-10 yrs) Full-time Georgia
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About the role

Design and develop a scalable financial data warehouse and real-time data pipelines using Kafka and Flink. Establish data governance, metadata frameworks, and ensure data quality across all batch and streaming platforms.

What they look for

Data Engineering Big Data Hive Spark Flink Kafka Data Warehousing Data Modeling ETL Data Governance Data Quality Financial Risk Fintech Streaming Technologies Business Intelligence

Requirements

Requires 5+ years of experience in data engineering with strong proficiency in Hive, Spark, Flink, and Kafka. Candidates must have significant experience within the fintech, banking, or financial risk sectors.

Full description

Senior Data Engineer – Financial Data

Location: Georgia Employment Type: Full-Time

About the Role

We are looking for a Senior Data Engineer to join our growing data team and take ownership of our financial data warehouse, real-time data platform and data governance initiatives.

You will work across DWH architecture, real-time streaming, data quality and financial data modelling, supporting critical risk, transaction and business intelligence use cases.

Key Responsibilities

  • Design and develop the Financial Data Warehouse, covering ODS, DWD, DWS and ADS layers.
  • Build scalable data models across users, transactions, repayments and risk domains.
  • Design and develop real-time data pipelines using Kafka and Flink.
  • Support real-time risk features, transaction monitoring and operational dashboards.
  • Ensure consistency between batch and real-time data through unified architectures.
  • Establish a Single Source of Truth (SSOT) for key business KPIs.
  • Build data governance, metadata and data quality frameworks.
  • Implement automated monitoring and quality checks across batch and streaming pipelines.

Requirements

  • 5+ years of experience in Data Engineering / Big Data development.
  • Strong hands-on experience with Hive, Spark and Flink.
  • Strong understanding of DWH architecture and ODS / DWD / DWS / ADS layering.
  • Production experience with Kafka, Flink or similar streaming technologies.
  • Experience with state management, exactly-once processing and late-arriving data.
  • Strong experience in ETL, data modelling and optimisation.
  • Experience building data governance and data quality frameworks.
  • Mandatory: Strong experience within banking, fintech, payments, lending, credit or financial risk.
  • Good understanding of loan origination, repayments, delinquency and risk data.

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