Senior Data Engineer - Banking Data Pipelines (Remote)

Visa Hunt; Poland; Hybrid; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Flexible working hours

Hybrid/Remote workplace

Technical equipment of your choice

Job summary

Softeta is seeking a Senior Data Engineer for a banking-sector client. You will design and optimize data ingestion, processing and storage, building scalable ETL/ELT pipelines using modern tools. The role requires SQL, Python, cloud platforms, and experience with data warehousing and streaming technologies.

Hybrid or remote work options are available, with emphasis on data quality, security and collaboration with analysts and stakeholders across business units.

Qualifications

• 3-5+ years in a Data Engineer role, financial industry experience is a plus.
• Solid SQL and Python experience.
• Experience with SQL and NoSQL databases.
• Cloud platforms (AWS/Azure/GCP).
• Kubernetes and Docker for orchestration.
• Experience with streaming pipelines (Kafka, Spark, Flink).
• Data warehousing solutions (Snowflake/BigQuery/Redshift).
• Familiarity with Airflow or dbt.
• Knowledge of data integrations (real-time, event-driven).
• Experience with DevOps and IaC security practices.
• Fluent English.

Responsibilities

• Design and improve data ingestion, processing, storage and sharing systems.
• Build data architectures for performance, scalability and reliability.
• Develop ETL/ELT pipelines with modern tools.
• Ensure data quality, security, availability and performance.
• Collaborate with analysts, engineers and stakeholders to meet data needs.
• Conduct code reviews and troubleshoot defects.
• Implement monitoring and alerting for data workflows.
• Gain expertise in banking processes and products.

Skills

SQL

Python

Cloud platforms

Kubernetes

Docker

Kafka / Streaming

Airflow / dbt

Data warehousing

English

Tools

Snowflake

BigQuery

Redshift

Airflow

dbt

Job description

Softeta is seeking a Senior Data Engineer for a banking-sector client. You will design and optimize data ingestion, processing and storage, building scalable ETL/ELT pipelines using modern tools. The role requires SQL, Python, cloud platforms, and experience with data warehousing and streaming technologies.

Hybrid or remote work options are available, with emphasis on data quality, security and collaboration with analysts and stakeholders across business units.