Cloud Data Architect
IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6–9 years
- Required Skills
- PythonSQLKafkaSparkCI/CDTerraformAzure DevOps
Requirements
- 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.
Responsibilities
- 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.
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