← к выдаче
разработка

Senior Data Engineer

Warsaw7 дн. назад

Коротко

Designs and improves end-to-end data solutions in banking across AWS and Oracle DB, using Airflow, dbt, and SAP Data Services; contributes to Data Mesh and · Needs: Hands-on SQL and Python; cloud platform experience (AWS, Azure, or GCP); data pipeline tools like Airflow or dbt; Oracle DB, SAP IQ, SAP Data Services, SAP

Описание от работодателя

Role Overview: We are looking for an experienced Senior Data Engineer to join a cross-functional Agile team within the banking domain. The role focuses on designing and improving end-to-end data solutions across AWS cloud and on-premises ( Oracle DB ) environments, working with Airflow , dbt , and SAP Data Services , and contributing to Data Mesh and Medallion architecture implementations.  Project/Client: Banking Location: Baltic States and Poland Citizen (remote) Start Date: ASAP Duration: 12 months Language: English Hourly rate: 30 - 32 EUR. B2B contract. Key Responsibilities: Design, implement, and improve data ingestion, processing, storage, and sharing within a Data Mesh platform across AWS cloud and legacy DWH environments Build and optimize ETL/ELT pipelines and data architectures using Airflow , dbt , and SAP Data Services Support modernization and migration of legacy data systems toward cloud-native architecture Ensure high standards of data quality, security, and performance across all data workflows Collaborate with analysts, engineers, and business stakeholders to deliver scalable data solutions Perform code reviews, implement monitoring and alerting, and resolve data pipeline defects Participate in the EOD ROTA rotation, with availability for incident resolution until 23:00-24:00 Must-Have Requirements: Proven hands-on experience with SQL and Python Hands-on experience with cloud platforms - AWS , Azure , or GCP Good understanding of data pipeline tools such as Airflow or dbt Working knowledge of enterprise data platforms: Oracle DB , SAP IQ , SAP Data Services , and SAP Business Objects Knowledge of solution integrations - real-time, message-based, and event-driven architectures - including bridging legacy systems with modern data platforms Exposure to test automation and DevOps practices, including infrastructure as code, security best practices, CI/CD , and SDLC Experience with Data Products deliveries, Medallion architecture , and Data Mesh architecture Strong communication and collaboration skills