Middle SDET โ€” Data Platform / Query Engine

$$$$

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2โ€“3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg โ€” enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Middle-level SDET to design and maintain automated tests for a large-scale distributed data platform. You will validate the correctness, performance, and reliability of the query engine, connectivity layer, and backend services across all major clouds.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers โ€” the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

RESPONSIBILITIES

  • Develop and maintain automated tests in Python / pytest for backend services, REST APIs, and distributed data components.
  • Write end-to-end, integration, and regression tests covering SQL query execution, data correctness, and platform APIs.
  • Support performance and load testing with JMeter, including workloads over JDBC / ODBC / Arrow Flightdrivers.
  • Validate data-intensive scenarios โ€” query plans, result correctness across data sources, metadata consistency, and behavior under concurrency.
  • Contribute to CI/CD test pipelines in Jenkins โ€” configure, maintain, and troubleshoot.
  • Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
  • Investigate failures across the stack โ€” query engine, distributed services, drivers, infrastructure โ€” and drive them to resolution with engineering.
  • Collaborate with US-based developers on testability and quality gates.

REQUIRED QUALIFICATIONS

  • Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
  • Programming: Strong proficiency in Python, including pytest, with a solid grasp of OOP and software design principles.
  • SQL & Data: Strong SQL skills and solid understanding of how relational and analytical data systems work.
  • Data-intensive testing experience: Hands-on experience testing data-intensive systems โ€” query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
  • Testing experience: 3+ years in backend/system test automation or SDET roles.
  • CI/CD & DevOps basics: Practical experience with Jenkins pipelines and deploying/maintaining test environments.
  • Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
  • Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
  • Version Control: Confident with Git / GitHub workflows.
  • English: Upper-Intermediate or higher (B2+) โ€” daily written and verbal communication with a US-based engineering team.
  • Availability: Able to work EU hours with a 2โ€“3 hour shift toward US West Coast time to ensure daily overlap with the client team.

DESIRED SKILLS

  • Experience testing REST APIs and backend microservices at scale.
  • Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines(e.g., Presto, Trino, or similar).
  • Understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
  • Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
  • Performance testing with JMeter or comparable load-testing tools.
  • Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
  • IaC tools such as Terraform.
  • Understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
  • Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Required skills experience

Python 3 years
PyTest 3 years
Object-Oriented Programming (OOP) 3 years
SQL 3 years

Required domain experience

Machine Learning / Big Data 2.5 years

Required languages

English B2 - Upper Intermediate
Data Visualisation, REST API, Azure, AWS, Git
Published 21 July
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