# Data Engineer

**Company:** [Softeta](http://jobs.workable.com/companies/pv575cTzKeknAR2ajQFWkf.md)
**Location:** Remote
**Workplace:** remote

[Apply for this job](http://jobs.workable.com/view/6694f616-de8e-4650-b679-e6b35539c5ab)

## Description

Softeta is a software engineering partner for finance, energy, industrial, and other high-stakes sectors. We specialize in building and modernizing backend-heavy, integration-critical systems where speed, accuracy, and reliability are non-negotiable. With 100+ AI and custom software experts across engineering hubs in Lithuania and Poland, we embed ourselves directly into client operations — delivering custom software, automation, and AI where they drive the most value.

We are seeking for a Senior Data Engineer for our client from the banking sector.

Job description:

-   Design, implement, and continuously improve systems for data ingestion, processing, storage, and sharing
-   Build and optimize data architectures for performance, scalability, and reliability
-   Develop and maintain ETL/ELT pipelines using modern tools and frameworks
-   Ensure seamless integration and synchronization across systems
-   Uphold high standards of data quality, security, availability, and performance
-   Collaborate with analysts, software engineers, and business stakeholders to understand data needs and deliver solutions
-   Perform code reviews, troubleshoot software, and fix defects
-   Implement monitoring and alerting for data workflows
-   Gain expertise in a variety of banking processes and products

## Requirements

-   3-5+ experience in a Data engineer position or a similar position, experience in financial industry considered as a Pluss.
-   Proven experience with SQL and Python; Other ETL engines are a plus
-   Experience with both SQL and NoSQL databases
-   Hands-on experience with the cloud platforms (AWS or Azure or GCP)
-   Experience with container orchestration tools (Kubernetes, Docker)
-   Understanding of streaming data pipelines and platforms (Kafka, Spark, Flink)
-   Familiarity with data pipeline tools like Airflow or dbt
-   Experience with data warehousing solutions (Snowflake, BigQuery, Redshift)
-   Knowledge of solution integrations (real-time, message-based, event-driven)
-   Exposure to test automation and DevOps practices, including infrastructure as code and security best practices
-   Experience within the risk or finance business domain is a strong advantage
-   Ability to take ownership and drive initiatives independently
-   Fluent English

## Benefits

-   Diverse and technically challenging projects.
-   Flexible working hours and a hybrid or remote workplace model.
-   Flexible schedule and an Agile/SCRUM environment.
-   Technical equipment that you can choose.