Staff SDET - Data Platform
New
M
MurmurationCivic Engagement Technology
United StatesFull-TimeStaff
Salary225324 USD per year
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Job Details
- Experience
- 12+ years
- Required Skills
- GraphQLPythonDynamoDBKafkaMongoDBNosqlSparkRESTful APIsAWS Lambda
Requirements
- 12+ years of experience in software engineering, data engineering, or SDET roles
- Deep proficiency in Python (or equivalent programming language) and experience writing production-quality, maintainable code
- Demonstrated experience designing and architecting complex test frameworks or automation systems
- Deep experience with streaming data pipelines, event-driven architectures, or distributed data systems (e.g., Kafka, Spark, Flink)
- Strong command of NoSQL databases (e.g., MongoDB, DynamoDB) and relational databases
- Experience testing or building systems in cloud-native, serverless environments (e.g., EventBridge, Lambda, asynchronous workflows)
- Experience testing GraphQL or REST APIs
- Demonstrated ability to operate with a high degree of autonomy
- Proven experience influencing testing or quality strategy across teams or an engineering organization
- Excellent debugging and analytical skills in complex, distributed, data-intensive environments
- Strong written and verbal communication skills
Responsibilities
- Rapidly develop a comprehensive understanding of our entire data platform (architecture, data flows, business logic, system interdependencies) to serve as the foundation for a testing strategy
- Work with our application QA Engineering Team to understand our existing testing strategy and tools to identify how to fill data testing gaps
- Design, architect, and lead the implementation of an integration testing framework for the Organizer application's streaming data platform
- Design automated validations that query and compare data across multiple storage systems (e.g., MongoDB, DynamoDB, Pinot) to ensure end-to-end data correctness
- Embed automated tests within CI/CD pipelines to establish regression baselines and continuously validate new feature development
- Design tests that rigorously account for eventual consistency, asynchronous processing, and time-based behaviors inherent to distributed systems
- Define and own the long-term quality and testing strategy for the data platform, aligning it with organizational reliability, observability, and engineering excellence goals
- Evaluate, select, and integrate tools, frameworks, and technologies to advance automation and data validation capabilities
- Implement automated performance and throughput benchmarks for critical pipeline components and own the standards by which results are evaluated
- Participate in engineering design reviews with a quality-first lens, ensuring testability, observability, and data correctness are built into systems from the start
- Proactively identify, investigate, and drive resolution of data quality issues and systemic reliability risks
- Lead post-incident reviews for data quality events, authoring clear timelines, facilitating root cause analysis, and driving follow-through on remediation action items
- Mentor engineers across the data platform and QA teams, establishing testing best practices and elevating the team's overall quality culture
- Represent the data platform's quality posture in cross-functional technical discussions and influence engineering standards across teams
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