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Senior Data Engineer (Python, AWS)
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingDesign, develop and optimize Python data pipelines for streaming market data with low latency
Integrate AWS services for ingestion, processing, storage and delivery of real-time and historical data
Provide L3 support for production incidents, including root cause analysis and fixes
Produce and maintain technical documentation for system understanding and knowledge transfer
From the employer’s posting
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
Provide L3 support for production incidents, performing root cause analysis and implementing corrective actions
Produce and maintain comprehensive technical documentation to support system understanding and knowledge transfer
Tools in this posting
- Python
- AWS
- DynamoDB
- NoSQL
- S3
Source — Tool mentions in context
We are seeking a Senior Data Engineer to join an established secondary market ETF analytics platform with over 7 years of production history. The team 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 with a Data Lakehouse and data pipeline architecture, the project is transitioning toward a "run-org" model, requiring someone who can confidently pick up and evolve an existing codebase. Responsibilities 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, ensuring rapid decision-making and iterative development Participate in regular coordination meetings with client managers and internal development teams to align deliverables Produce and maintain comprehensive technical documentation to support system understanding and knowledge transfer Provide L3 support for production incidents, performing root cause analysis and implementing corrective actions Evaluate and adopt emerging technologies and methodologies to enhance pipeline performance and reliability Requirements 3+ years of experience in Data Software Engineering Proficiency in Python development within data engineering environments, emphasizing scalable and maintainable code Expertise in designing and implementing data lakehouse architectures and real-time streaming data pipelines Skills in 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 Capability to provide Level 3 production support for critical data engineering systems with strong troubleshooting abilities Understanding of financial or banking domain concepts, enabling effective collaboration with business stakeholders English proficiency at an Upper-Intermediate level (B2) or higher
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 4, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
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About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
We are seeking a Senior Data Engineer to join an established secondary market ETF analytics platform with over 7 years of production history. The team 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 with a Data Lakehouse and data pipeline architecture, the project is transitioning toward a "run-org" model, requiring someone who can confidently pick up and evolve an existing codebase. Responsibilities 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, ensuring rapid decision-making and iterative development Participate in regular coordination meetings with client managers and internal development teams to align deliverables Produce and maintain comprehensive technical documentation to support system understanding and knowledge transfer Provide L3 support for production incidents, performing root cause analysis and implementing corrective actions Evaluate and adopt emerging technologies and methodologies to enhance pipeline performance and reliability Requirements 3+ years of experience in Data Software Engineering Proficiency in Python development within data engineering environments, emphasizing scalable and maintainable code Expertise in designing and implementing data lakehouse architectures and real-time streaming data pipelines Skills in 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 Capability to provide Level 3 production support for critical data engineering systems with strong troubleshooting abilities Understanding of financial or banking domain concepts, enabling effective collaboration with business stakeholders English proficiency at an Upper-Intermediate level (B2) or higher
Source details
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- Location & working pattern
Poland
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