savvymoney - Senior Data Engineer (EU, EMEA Remote)
Requirements
• 8+ years of experience in data engineering, backend engineering, or a hybrid role • Strong hands-on experience with AWS, including: • AWS Step Functions • Amazon Athena • Amazon Redshift • Experience building batch data pipelines and ETL systems at scale • Java (for microservices development) • Python (for data pipelines and Glue jobs) • Experience working with containerized services and orchestration via Amazon ECS • Experience designing or working within microservices architectures • Familiarity with event-driven systems (e.g., SQS, EventBridge) • Strong SQL skills and experience optimizing analytical queries • Experience with distributed processing frameworks (e.g., Spark via Glue) • Deep understanding of: • Data modeling (analytical and operational) • Partitioning and storage strategies • Performance tuning across multiple data systems • Experience with Apache Airflow or similar orchestration tools • Experience with ClickHouse at scale (schema design, query optimization) • Experience with financial or credit data systems • Familiarity with data quality frameworks • AWS certifications (Solutions Architect, Developer, or Data Analytics)
Responsibilities
• Design, build, and own batch-oriented data pipelines and ETL workflows using: • AWS Glue for distributed processing • AWS Lambda and AWS Step Functions for orchestration • Amazon S3 as the central data lake • Develop and optimize ingestion pipelines using AWS-native services such as AppFlow, DMS, and limited use of Kinesis/Firehose for ingestion • Build and maintain analytical data models and query layers using: • Amazon Athena • Amazon Redshift • Design and integrate data workflows with backend microservices running on Amazon ECS • Collaborate with backend engineers to build and extend microservices that expose data capabilities via APIs • Contribute to event-driven architectures using services such as EventBridge to coordinate data processing and system interactions • Ensure data quality, lineage, and observability through validation frameworks, monitoring, and alerting • Optimize performance across the stack (Glue jobs, Athena queries, Redshift workloads, ClickHouse schemas) • Implement best practices for: • Infrastructure as Code (Serverless/CloudFormation, Terraform) • CI/CD pipelines for data and services • Security, governance, and PII handling • Mentor engineers and contribute to architectural decisions and technical strategy
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