Data Architect, Information Technology Services
- Bengaluru
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Client
Project overview
DataArt's specialists focus on data streaming and sourcing solutions to ensure data processing necessary for trading operations.
Team
Position overview
This is a hands-on architectural role focused on producing clear, structured, and forward-looking designs. Your work will directly shape how data is governed, traced end-to-end, and used across the organisation.
Responsibilities
- Evaluate the current data architecture across pipelines, storage, data flows, and integrations, and identify opportunities to optimise for performance, scalability, and maintainability.
- Design and deliver data lineage solutions that provide end-to-end visibility into how data originates, moves, and transforms across the platform, ensuring traceability for regulatory and operational purposes.
- Establish data classification and sensitivity policies in alignment with information security requirements.
- Work with platform engineering to define event-driven data ingestion patterns and to align on shared compute strategies.
- Contribute to a data product roadmap that captures key milestones, governance checkpoints, and architectural priorities.
- Collaborate with engineering and business subject matter experts to align the architecture with product requirements and evolving ML and AI workflows.
- Provide architectural guidance on access management, data privacy, and compliance controls. Produce clear visual and written documentation suitable for both technical and non-technical audiences.
Requirements
- Demonstrated experience as a Data Architect, Senior Data Engineer within modern cloud environments.
- Deep knowledge of data modelling, ETL and ELT processes, data governance frameworks, data lineage, and distributed data systems.
- Hands-on experience designing and implementing lineage and cataloguing solutions.
- Hands-on experience with platforms such as Databricks, Snowflake, or comparable lakehouse and warehouse technologies.
- Familiarity with transformation and orchestration tools.
- Ability to produce clear architectural materials and communicate complex concepts to varied audiences.
- Comfort working in enterprise environments.
- A collaborative working style with experience bridging engineering, product, and business functions.
- Exposure to ML and AI workflows, MLflow, or model-driven architectures is an advantage. Knowledge of data lakehouse principles and unified governance frameworks.
- Awareness of information security best practices as they apply to data architecture.
- Ability to influence without formal authority and guide teams through ambiguity.
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