We are seeking an experienced Data Architect with strong expertise in Databricks, Python, and AWS to design, develop, and implement scalable, secure, and high-performance data architecture solutions.

The ideal candidate will have extensive experience designing cloud-based data platforms, developing data pipelines, implementing data integration solutions, and optimizing large-scale data processing environments.

Required Skills

• Strong experience with Databricks architecture and development.
• Advanced Python programming and development.
• Extensive experience with AWS cloud services.
• Data architecture, data modeling, and database design.
• Designing and developing scalable ETL/ELT pipelines.
• Data ingestion, transformation, and integration.
• Apache Spark / PySpark.
• Databricks Delta Lake and Lakehouse architecture.
• AWS S3, Glue, Lambda, IAM and related services.
• SQL and database performance optimization.
• Data governance, security, and access management.
• CI/CD, Git and deployment automation.

Key Responsibilities

• Design and implement enterprise-level data architecture using Databricks and AWS.
• Develop scalable data pipelines using Python, PySpark, and Spark SQL.
• Architect cloud-based data lake and lakehouse solutions.
• Integrate data from multiple sources into centralized data platforms.
• Implement ETL/ELT workflows and optimize data processing.
• Establish data governance, security, and quality standards.
• Optimize Databricks workloads and AWS infrastructure for performance and scalability.
• Collaborate with engineering, business, and technical teams.
• Prepare technical architecture documentation and implementation guidelines.

Candidate Requirements

• Strong hands-on Databricks, Python, and AWS experience.
• Experience designing enterprise-scale data platforms.
• Excellent communication and technical documentation skills.
• Ability to work independently in a remote environment.