11/11/2026 updated
AB
100 % available
Data Engineer | Python | Snowflake | Databricks | ETL Pipelines | Data Architect
Slovakia
Only remote
Master's degree (in progress), Information Systems and DevOpsAzure DatabricksdbtAzure DevOpsApache AirflowGoogle BigQueryApache ImpalaData WarehousingPostgreSQLAzure Data LakePL-SQLSQL DatabasesDatabase EnginesAzure Data FactorySnowflakeApache Spark
ETL & Pipeline Engineering
Over 3 years of production ETL experience in banking using Python, SQL, Apache Spark, AWS Glue, and Apache Airflow. Design and ownership of end-to-end pipelines for high-volume financial data under strict compliance requirements, including incremental-load infrastructure with SCD2/CDC patterns.
Apache Spark & Lakehouse Architecture
Hands-on experience with Apache Spark and Apache Iceberg for large-scale data processing. Migration of core financial pipelines from Delta Lake to an Apache Iceberg/Polaris catalog architecture with zero disruption to daily financial close operations.
Apache Airflow Orchestration
Development and ownership of a custom Apache Airflow framework featuring dynamic DAGs from PostgreSQL configuration, custom operators and sensors, and cross-DAG dependencies. Led the orchestration migration from YARN to Kubernetes and upgraded Airflow 2 to 3.
AWS Cloud Services
Practical experience with AWS Glue, Amazon S3, AWS Aurora (PostgreSQL), RDS, DynamoDB, EC2, and boto3 for cloud-based data engineering and automation tasks.
GCP & BigQuery
Building incremental batch pipelines on GCP using Cloud Storage, Spark on Dataproc, and BigQuery, orchestrated with Airflow and provisioned via Terraform.
Databases & Data Warehousing
Proficiency in Oracle, PostgreSQL, and MongoDB. Experience with data warehousing for IFRS financial reporting, including redesigning IFRS reporting tables for improved query performance.
PL/SQL Development
Development of Oracle PL/SQL functions and packages for critical financial data, supporting ETL processes and database optimisation in a banking environment.
DevOps & Infrastructure
Experience with Docker, Kubernetes, Terraform, Jenkins, GitLab CI, and Git for containerisation, infrastructure-as-code, and CI/CD pipeline management.
Python & SQL
Advanced skills in Python and SQL for data engineering, automation, and financial data processing. Additional experience with Node.js and PL/SQL.
Over 3 years of production ETL experience in banking using Python, SQL, Apache Spark, AWS Glue, and Apache Airflow. Design and ownership of end-to-end pipelines for high-volume financial data under strict compliance requirements, including incremental-load infrastructure with SCD2/CDC patterns.
Apache Spark & Lakehouse Architecture
Hands-on experience with Apache Spark and Apache Iceberg for large-scale data processing. Migration of core financial pipelines from Delta Lake to an Apache Iceberg/Polaris catalog architecture with zero disruption to daily financial close operations.
Apache Airflow Orchestration
Development and ownership of a custom Apache Airflow framework featuring dynamic DAGs from PostgreSQL configuration, custom operators and sensors, and cross-DAG dependencies. Led the orchestration migration from YARN to Kubernetes and upgraded Airflow 2 to 3.
AWS Cloud Services
Practical experience with AWS Glue, Amazon S3, AWS Aurora (PostgreSQL), RDS, DynamoDB, EC2, and boto3 for cloud-based data engineering and automation tasks.
GCP & BigQuery
Building incremental batch pipelines on GCP using Cloud Storage, Spark on Dataproc, and BigQuery, orchestrated with Airflow and provisioned via Terraform.
Databases & Data Warehousing
Proficiency in Oracle, PostgreSQL, and MongoDB. Experience with data warehousing for IFRS financial reporting, including redesigning IFRS reporting tables for improved query performance.
PL/SQL Development
Development of Oracle PL/SQL functions and packages for critical financial data, supporting ETL processes and database optimisation in a banking environment.
DevOps & Infrastructure
Experience with Docker, Kubernetes, Terraform, Jenkins, GitLab CI, and Git for containerisation, infrastructure-as-code, and CI/CD pipeline management.
Python & SQL
Advanced skills in Python and SQL for data engineering, automation, and financial data processing. Additional experience with Node.js and PL/SQL.
Languages
EnglishFluentGeorgianNative speaker
Project history
Architected and owned production ETL pipelines using Apache Spark, AWS Glue, Airflow, and Python for high-volume financial data under strict compliance requirements. Migrated core financial pipelines from Delta Lake to Apache Iceberg/Polaris catalog architecture with zero disruption. Replaced a hardcoded IFRS balance-generation module with a config-driven transformation architecture. Built and owned a custom Airflow framework with dynamic DAGs, custom operators, and cross-DAG dependencies; moved orchestration from YARN to Kubernetes and upgraded Airflow 2 to 3. Built incremental-load infrastructure (SCD2/CDC) for provisioning and credit card data, and new ETL for sovereign and yield-curve data.
Built an incremental batch pipeline on GCP (Cloud Storage to Spark on Dataproc to BigQuery) with Airflow and Terraform, plus a Python/boto3 CLI for AWS automation (RDS, DynamoDB).
Validated data quality across core financial datasets, resolving discrepancies before reporting. Transitioned into ETL work using Spark, AWS Glue, and Apache Airflow.