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Data Architect – AI & Data Platform Team
Luxoft is growing its advanced AI delivery capability and is seeking a talented Data Architect to join an innovative, high-impact project team. This role offers an opportunity to work at the intersection of data, cloud, and artificial intelligence, helping global clients extract real business value from their data.
At Luxoft, you’ll contribute to cutting-edge AI programs that deliver measurable outcomes—collaborating with top engineers, data scientists, and innovators across international teams. Our culture thrives on technical excellence, continuous learning, and the freedom to shape architecture decisions.
The ideal candidate is passionate about building modern data platforms, supporting evolving AI use cases, and creating scalable, future-ready architectures in a supportive and collaborative environment.
About the Role
As a Data Architect, you’ll design and implement robust data architectures that support machine learning and AI solutions. Your work will ensure data is structured, accessible, secure, and optimised for analytics and model development. In tandem with data and ML engineers, you’ll play a central role in constructing high-quality data ecosystems that drive innovation.
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Key Responsibilities
- Design and maintain conceptual, logical, and physical data models, including relational schemas, graph models, and time-series structures
- Define scalable data storage architectures using a mix of:
- Relational databases
- NoSQL systems
- Data lakes
- Data warehouses
- Develop and oversee data pipelines, including:
- ETL/ELT processes
- Batch workflows
- Real-time streaming integrations
- Establish data governance frameworks to ensure:
- Data quality
- Compliance with regulatory standards
- Privacy and security
- Implement metadata management and data lineage practices to ensure transparency across data flows
- Collaborate closely with data engineers, data scientists, and ML engineers to align architecture with AI and ML needs
- Optimise performance, cost-efficiency, and scalability of data platforms in cloud environments
- Continuously evaluate and adopt modern data technologies, frameworks, and architectural best practices
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Your Experience
Required
- Strong expertise in data modelling, schema design, SQL optimisation, and working with:
- Relational databases (e.g., PostgreSQL, Oracle)
- NoSQL systems (e.g., MongoDB, Cassandra, DynamoDB)
- Hands-on experience building and optimising data pipelines using:
- ETL/ELT tools
- Scripting languages (e.g., Python, SQL, Spark)
- Solid understanding of:
- Cloud data platforms (AWS Glue, Google BigQuery, Azure Synapse)
- Distributed data architectures (e.g., scalability, fault tolerance)
- Knowledge of data governance, security, and compliance best practices (e.g., GDPR, CCPA)
Nice to Have
- Experience supporting AI or machine learning initiatives
- Familiarity with data cataloguing and metadata governance tools, such as:
- Collibra
- Alation
- Apache Atlas
- Exposure to knowledge graphs, ontologies, or semantic data modelling
- Understanding of modern data architecture approaches:
- Data mesh
- Lakehouse architectures
- Event-driven systems
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