This is a fully remote position, open to applicants in Poland.

• Design, implement, and continuously enhance systems for data ingestion, processing, storage, and sharing.

• Construct and refine data architectures to ensure optimal performance, scalability, and reliability.

• Develop and maintain ETL/ELT pipelines utilizing modern tools and frameworks.

• Ensure seamless integration and synchronization among various systems.

• Maintain high standards of data quality, security, availability, and performance.

• Collaborate with analysts, software engineers, and business stakeholders to comprehend data requirements and deliver effective solutions.

• Conduct code reviews, troubleshoot software issues, and resolve defects.

• Implement monitoring and alerting mechanisms for data workflows.

• Acquire expertise in a range of banking processes and products.

• 3-5+ years of experience in a Data Engineer role or a comparable position; experience in the financial industry is considered a plus.

• Demonstrated expertise in SQL and Python; familiarity with other ETL engines is advantageous.

• Experience with both SQL and NoSQL databases.

• Practical experience with cloud platforms (AWS, Azure, or GCP).

• Proficiency with container orchestration tools (Kubernetes, Docker).

• Understanding of streaming data pipelines and platforms (Kafka, Spark, Flink).

• Familiarity with data pipeline tools such as 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 in the risk or finance business domain is a significant advantage.

• Capability to take ownership and drive initiatives independently.

• Proficient in English.

• 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.

Data Engineer

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