data engineer for ETF analytics

The established secondary-market ETF analytics platform has over seven years of production history. It ingests daily trading reports from multiple sources, including file providers, market data providers, spread data, and bookings, to produce analytics outputs. Built entirely on Python and AWS, the project uses a Data Lakehouse and data pipeline architecture and is transitioning toward a «run-org» model.

• Design, develop, and optimize Python-based data pipelines to process streaming market data with minimal latency
• Integrate AWS cloud services to support ingestion, processing, storage, and delivery of real-time and historical data
• Collaborate within a small agile team of 3 to 5 engineers to support rapid decision-making and iterative development
• Participate in regular coordination meetings with client managers and internal development teams to align deliverables
• Produce and maintain technical documentation to support system understanding and knowledge transfer
• Provide L3 support for production incidents, perform root cause analysis, and implement corrective actions
• Evaluate and adopt emerging technologies and methodologies to enhance pipeline performance and reliability

• At least 3 years of experience in Data Software Engineering
• Proficiency in Python development in data engineering environments, with an emphasis on scalable and maintainable code
• Expertise in designing and implementing data lakehouse architectures and real-time streaming data pipelines
• Experience integrating and managing AWS services, including S3, ECS, and EC2
• Competency in working with Lambda, Step Functions, and EventBridge
• Familiarity with CloudWatch and DynamoDB for monitoring and NoSQL data management
• Ability to provide Level 3 production support for critical data engineering systems, with strong troubleshooting skills
• Understanding of financial or banking domain concepts
• English proficiency at Upper-Intermediate level (B2) or higher

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