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Pythian

Cloud migration and managed analytics services

Data Architect

Data EngineeringUpdated on Nov 13
Full-timeRemote in UKNo salary listed

About the Job

Requirements

  • Eight or more years of experience in data engineering, including at least three years owning architecture and design decisions.
  • Demonstrated hands-on delivery, including the ability to identify data platforms designed and built.
  • Deep hands-on experience with Databricks or Microsoft Fabric, and working knowledge of the other.
  • Strong Spark and SQL skills, and solid Python or an equivalent language used in production data work.
  • Production experience with Delta Lake, medallion architecture, and lakehouse patterns.
  • Experience with Power BI, including how the semantic model is built and where it should live.
  • Dimensional and semantic modeling skills, including the ability to explain where business logic belongs and why.
  • Working knowledge of data governance, including classification, lineage, cataloging, and access control.
  • Experience applying CI/CD, version control, and testing practices to data work.

Responsibilities

  • Design and develop end-to-end cloud-based solutions focused on applications and data, with an understanding of infrastructure.
  • Work on complex cloud-based projects involving collection, parsing, management, analysis, and visualization of very large datasets.
  • Translate functional and technical requirements into detailed designs.
  • Write high-performance, reliable, and maintainable code.
  • Develop test automation and project-related tooling.
  • Work with project leads to understand testing requirements and lead the creation and execution of test automation.
  • Develop test scenarios and test cases based on requirements.
  • Analyze potential issues, perform root cause analysis, and assign issues for resolution.
  • Follow up with engineering team members to ensure fixes are completed.
  • Review bug descriptions, functional requirements, and design documents, and incorporate them into test plans and test cases.
  • Perform data processing requirements analysis.
  • Tune performance for batch and real-time data processing.
  • Secure components of clients’ cloud data platforms.
  • Diagnose and troubleshoot operational issues.
  • Conduct health checks and configuration reviews.
  • Develop data pipelines for ingestion, transformation, and cleansing.
  • Integrate data flows with external systems.
  • Integrate with data access tools and products.
  • Implement foundational CI/CD for infrastructure components, data pipelines, and custom data applications.
  • Provide operational visibility across the data platform, from infrastructure and pipelines to machine learning applications.
  • Assist client application developers and advise on efficient data access and manipulation.
  • Define and implement efficient operational processes.

About the Company

Pythian

Cloud migration and managed analytics services

Pythian helps organizations move, manage, and analyze data and IT infrastructure. It provides cloud migration, managed services, and advanced analytics to help businesses use cloud platforms such as Google Cloud, AWS, and Azure. Its solutions include moving data and applications to the cloud, running and monitoring those systems, and turning data into insights through machine learning, artificial intelligence, and data science. Pythian differentiates itself by offering a fully managed analytics platform that unifies a company’s data across sources and by combining expert consulting with ongoing operations to ensure data systems run smoothly. The company’s goal is to enable enterprises to improve decision-making, reduce IT friction, and drive growth by leveraging cloud technology and data analytics.

Company size
501-1,000
Company stage
Early VC
Total funding
$21M
Headquarters
Ottawa, Canada
Founded
1997

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