Senior Databricks Solution Architect

Description

We are seeking a Senior Databricks Architect to design, implement, and optimize enterprise-scale data platforms using the  Databricks Lakehouse Platform . The ideal candidate will have deep expertise in Databricks architecture, Apache Spark, Delta Lake, data engineering, cloud platforms, and enterprise data solutions.

Key Responsibilities Design and architect  Databricks Lakehouse solutions  for large-scale enterprise data platforms.

Lead end-to-end Databricks implementation, including architecture, development, deployment, and optimization.

Define Databricks workspace architecture, cluster strategies, security models, and operational standards.

Design and develop scalable data pipelines using  Databricks, Apache Spark, PySpark, SQL, and Delta Lake .

Implement data ingestion frameworks supporting batch and real-time data processing.

Design Delta Lake architectures including:

Delta tables

Medallion architecture (Bronze/Silver/Gold layers)

Data quality frameworks

Schema evolution and optimization

Perform Databricks performance tuning:

Cluster optimization

Spark job optimization

Query tuning

Cost optimization

Implement Databricks governance and security using:

Unity Catalog

Access controls

Data lineage

Audit capabilities

Lead migration projects from legacy data platforms to Databricks Lakehouse.

Define best practices for Databricks CI/CD, DevOps, and environment management.

Collaborate with data engineers, data scientists, analysts, and enterprise architects.

Provide technical guidance, architecture documentation, and design reviews.

Skills & Experience Strong experience in data engineering, big data, or solution architecture.

Strong hands-on experience with  Databricks Platform .

Expert knowledge of:

Apache Spark

PySpark / Scala

Delta Lake

SQL

Data Lakehouse architecture

ETL/ELT development

Experience designing and delivering enterprise Databricks solutions.

Strong experience with cloud platforms:

Azure Databricks (preferred)

AWS Databricks

Google Cloud Databricks

Experience with:

Databricks Workflows

Jobs orchestration

Notebooks

Repos

Cluster management

Unity Catalog

Preferred Skills Databricks Certified Data Engineer Professional / Databricks Certified Architect.

Experience with:

MLflow

Databricks Machine Learning

Feature Store

Model deployment

MLOps

Knowledge of streaming technologies:

Structured Streaming

Kafka

Experience with data governance, compliance, and enterprise security frameworks.

Key Competencies Strong Databricks architecture and implementation expertise.

Ability to design scalable and cost-efficient Lakehouse solutions.

Strong troubleshooting and performance optimization skills.

Ability to lead technical discussions with enterprise stakeholders.