Remote Data Engineer

Description:

• Design, implement, and 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.
• Perform code reviews, troubleshoot software, and fix defects.
• Implement monitoring and alerting for data workflows.
• Gain expertise in banking processes and products.

Requirements:

• 3-5+ years of experience in a Data Engineer position or similar, with financial industry experience as a plus.
• Proven experience with SQL and Python; familiarity with other ETL engines is a plus.
• Experience with both SQL and NoSQL databases.
• Hands-on experience with cloud platforms (AWS, 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.
• Experience in the risk or finance business domain is a strong advantage.
• Ability to take ownership and drive initiatives independently.
• Fluent in 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.