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Team: IT
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Data Architect based in India.
This role offers the opportunity to design and shape modern, scalable cloud-based data ecosystems for complex enterprise use cases.
You will work closely with stakeholders to translate business needs into robust technical architectures across data engineering, analytics, and AI-driven solutions.
The position involves hands-on engagement with cutting-edge Azure data services, including Databricks, Data Factory, and Synapse.
You will contribute to proof-of-concept development, architecture decisions, and the evolution of data platforms in a fast-paced environment.
A strong focus is placed on performance optimization, cost efficiency, and best practices in cloud-native data engineering.
The environment is highly collaborative, combining strategic architectural thinking with practical engineering execution.
Accountabilities:
- Lead architectural discussions and workshops with clients to gather business and technical requirements and design scalable cloud data solutions.
- Translate requirements into end-to-end technical architectures for data lakes, lakehouses, BI, and ML/AI workloads.
- Design, build, and support data engineering solutions using Azure Databricks, Azure Data Factory, ADLS Gen2, and Synapse Serverless.
- Develop PoCs, prototypes, and MVPs for innovative cloud and big data solutions, including technology evaluation and scouting.
- Implement and optimize large-scale data pipelines, ensuring performance tuning (especially in Apache Spark environments).
- Support production systems through monitoring, troubleshooting, and ongoing enhancements when required.
- Drive cost optimization initiatives and ensure efficient use of cloud resources.
- Create and maintain comprehensive technical documentation and architecture guidelines.
- 6–9 years of experience in data engineering, with strong exposure to enterprise-scale cloud data platforms.
- Deep expertise in Apache Spark, including performance tuning and optimization techniques.
- Strong hands-on experience with Delta Lake and Databricks on Azure.
- Advanced proficiency in Python and complex SQL for data processing and transformation.
- Extensive experience building data pipelines using Azure Data Factory.
- Solid knowledge of Azure data services such as ADLS Gen2 and Synapse Serverless.
- Proven ability to architect cloud-based data platforms and evaluate trade-offs between tools (Databricks, Snowflake, MS Fabric, etc.).
- Experience with streaming technologies such as Kafka or Spark Structured Streaming.
- Familiarity with cloud concepts including networking, security, and monitoring in Azure environments.
- Hands-on experience with DevOps practices, CI/CD pipelines, Infrastructure as Code (Terraform), preferably using Azure DevOps.
- Exposure to Microsoft Fabric is considered a strong advantage.
- Strong analytical thinking, problem-solving skills, and ability to communicate technical concepts clearly.
- Competitive compensation aligned with experience and market standards
- Fully remote working arrangement
- Opportunity to work on advanced cloud-native data platforms and large-scale enterprise projects
- Exposure to cutting-edge Azure data and AI technologies
- Dynamic, innovation-driven project environment
- Continuous learning and upskilling opportunities
- Collaborative international team setup.
Requirements:
Benefits:
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