Job Details

About the Role

We are seeking a seasoned Solution Architect with a strong background in designing and implementing scalable data and cloud architectures. The ideal candidate will have hands-on experience with Databricks, modern data platforms, and enterprise-grade cloud solutions. You’ll collaborate with cross-functional teams to define technical roadmaps, architect high-performing solutions, and drive innovation across analytics and data-driven platforms.

Key Responsibilities

• Design and lead implementation of end-to-end cloud-native data platforms leveraging tools such as Databricks, Delta Lake, and MLflow.
• Define architecture for large-scale ETL/ELT pipelines, data lakes, and real-time/streaming data solutions.
• Collaborate with data engineers, data scientists, and stakeholders to convert business goals into scalable technical solutions.
• Integrate Databricks notebooks, Apache Spark, and cloud-native services (e.g., AWS Glue, Azure Data Factory) for batch and real-time data processing.
• Implement governance and data security using tools like Unity Catalog, IAM, and encryption at rest/in transit.
• Define integration patterns using REST APIs, event-driven messaging (Kafka/Pub/Sub), and distributed systems design.
• Participate in architectural reviews and performance tuning across distributed compute frameworks.
• Stay updated on emerging tools and technologies in data architecture, cloud infrastructure, and ML Ops.

Required Qualifications

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
• 10+ years of experience in enterprise software or data architecture roles.
• Strong hands-on experience with Databricks, Apache Spark, and Delta Lake.
• Proficiency in at least one cloud platform (AWS, Azure, or GCP), with experience in services like S3, ADLS, BigQuery, or Redshift.
• Familiarity with streaming platforms such as Kafka, Kinesis, or Azure Event Hubs.
• Experience designing and deploying data lakehouses or analytics platforms.
• Strong understanding of data modeling, data governance, and pipeline orchestration (Airflow, dbt, or similar).
• Skilled in performance optimization, data security best practices, and cloud cost management.
• Excellent communication skills for stakeholder management and cross-functional collaboration.

Preferred Skills

• Preferred certifications in Databricks, AWS/Azure/GCP Solution Architecture, or TOGAF.
• Knowledge of ML/AI workflows, model versioning, and ML Ops practices.
• Experience with Unity Catalog, Great Expectations, or data quality frameworks.
• Prior work in regulated environments (e.g., healthcare, finance, insurance) is a plus.