iXceed Solutions
Data Architect
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Senior Technology Architect / Data Architect
Location: London, UK
Work Mode: Hybrid – 10 days onsite per month
Contract Duration: 6-12 Months
Experience: 10+ Years
Role Summary
We are looking for an experienced Senior Technology Architect / Data Architect to design, build, and operate scalable data pipelines and data products, supporting a modern Data Mesh architecture.
The role involves integrating legacy systems with cloud-native platforms to enable analytics, reporting, and domain-owned data products. The ideal candidate will have strong hands-on expertise in Databricks, Apache Spark, Kafka, AWS data services, and legacy data integration, along with a solid understanding of modern data architecture and engineering practices.
Key Responsibilities
- Design, develop, and maintain batch and streaming data pipelines from legacy mainframe DB2 and on-premises SQL Server systems into an AWS-based data lake.
- Implement real-time data ingestion using Confluent Kafka and land data into Amazon S3.
- Develop scalable data transformation and analytics pipelines using Databricks, PySpark, and SQL.
- Implement the Medallion Architecture (Bronze, Silver, and Gold layers).
- Design and deliver reusable, high-quality data products aligned with Data Mesh principles.
- Ensure data quality, reliability, security, and governance across data pipelines.
- Integrate legacy data platforms with modern cloud-native architecture.
- Collaborate with domain teams, platform teams, and stakeholders to enable self-service analytics and data consumption.
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Required Skills & Experience
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- 10+ years of experience in technology/data architecture or data engineering.
- Strong expertise in Databricks, Apache Spark, PySpark, and SQL.
- Hands-on experience with Kafka / Confluent Kafka and streaming technologies.
- Strong understanding of AWS data services, particularly Amazon S3.
- Experience integrating legacy data sources, especially DB2/Mainframe and SQL Server.
- Strong understanding of Data Lake Architecture and modern data engineering best practices.
- Knowledge of Data Mesh concepts and domain-oriented data products.
- Experience designing scalable batch and real-time data pipelines.
Good to Have
- Banking or Financial Services domain experience.
- Knowledge of data governance and metadata management.
- Exposure to regulatory reporting and enterprise data platforms.
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