Description

Requirements

10 or more years of experience in enterprise data solutions architecture and multi-cloud platform design.

Proficiency in Azure Databricks, Azure Synapse Analytics, and modern Lakehouse architectures.

Experience with distributed data processing and streaming frameworks using PySpark, Kafka, and Apache Airflow.

Experience in enterprise data warehousing and modeling with Snowflake, ADLS Gen2, and Azure Data Factory.

Experience with AWS cloud data services including AWS Glue, Lambda, and cloud data migration strategies.

Experience in Infrastructure as Code using Terraform, Azure DevOps CI/CD automation, and Power BI integration.

Excellent verbal and written communication skills.

Responsibilities

Architect end-to-end cloud data platforms and scalable Lakehouse ecosystems across Azure and AWS environments.

Design high-throughput batch and real-time streaming data ingestion pipelines utilizing Kafka and PySpark.

Define dimensional data models, star schemas, and metadata management frameworks for advanced analytics.

Implement Infrastructure as Code deployments and automated CI/CD pipelines using Terraform and Azure DevOps.

Execute performance optimization techniques including data partitioning, clustering, and distributed workload tuning.

Establish robust enterprise data governance, automated data quality validation, and cloud security frameworks.

Integrate enterprise business intelligence solutions and AI/ML data enablement architectures with Power BI

Key Skills

Education

Any Gradute