Data Engineering - Databricks Professional Services

Accelerate your data transformation journey with our Databricks Professional Services for AWS.

Our certified data engineers and cloud architects help organizations design, implement, and optimize Databricks Lakehouse Platforms on AWS — unifying data engineering, analytics, and machine learning at scale.

We deliver end-to-end solutions that modernize your data architecture, streamline ETL pipelines, and empower teams with real-time insights across structured and unstructured data.

Our core services include:

• Databricks Architecture & Implementation: Design and deploy scalable Databricks workspaces integrated with AWS services such as S3, Glue, and Redshift.
• Data Pipeline Development: Build and automate ETL/ELT workflows using PySpark, Delta Live Tables, and AWS-native tools.
• Performance Optimization: Tune clusters, jobs, and queries for maximum speed and cost efficiency.
• Data Governance & Security: Implement access controls, Unity Catalog, and compliance frameworks across your data lakehouse.
• Machine Learning & AI Enablement: Operationalize ML models on Databricks with Amazon SageMaker or native MLflow integration.
• Migration & Modernization: Transition from legacy Spark, Hadoop, or on-prem data systems to Databricks on AWS.

Key Benefits:

• Unified data platform for engineering, analytics, and AI
• Faster, automated data pipelines with Delta Lake reliability
• Scalable, cost-optimized compute leveraging AWS infrastructure
• Certified experts in both Databricks and AWS ecosystems

Whether you’re building a new lakehouse or optimizing an existing Databricks environment, our Data Engineering – Databricks Professional Services help you harness the full power of cloud-scale analytics on AWS.