Databricks Architect

The Job Description

Databricks Architect – Technical Job Description

We are seeking a Databricks Architect with strong expertise in designing, solutioning, and delivering enterprise-scale data and analytics platforms on cloud. The role requires deep technical leadership in architecting modern data ecosystems, defining target-state architectures, and driving end-to-end solution delivery using Databricks Lakehouse.

Key Responsibilities

Lead solution architecture and technical design for enterprise data, analytics, AI, and modernization programs. Design and implement scalable Databricks Lakehouse solutions leveraging Delta Lake, Apache Spark, Unity Catalog, and Medallion Architecture. Define end-to-end architectures covering data ingestion, transformation, governance, security, analytics, and consumption layers. Translate business requirements into scalable, cost-effective, and high-performance technical solutions. Drive cloud data platform modernization and migration initiatives from legacy data warehouses and Hadoop ecosystems. Architect batch, streaming, and near real-time data processing pipelines using PySpark, Spark SQL, Kafka, and cloud-native services. Establish architecture standards, reusable frameworks, reference architectures, and best practices. Lead performance tuning, capacity planning, cost optimization, and platform scalability initiatives. Collaborate with business stakeholders, delivery teams, and cloud architects to develop winning solution strategies and implementation roadmaps. Provide technical leadership during pre-sales, RFP responses, solution estimations, and client workshops. Required Technical Expertise

Deep expertise in Databricks, Apache Spark, Delta Lake, PySpark, Spark SQL, and Unity Catalog. Strong experience in solution architecture, technology selection, and enterprise data platform design. Expertise across Azure, AWS, or GCP data services and cloud-native architectures. Hands-on experience with Data Governance, Security, Data Quality, Metadata Management, and Observability frameworks. Strong knowledge of ETL/ELT patterns, Data Modeling, Data Warehousing, Data Mesh, and Lakehouse architectures. Experience with Terraform, CI/CD, DevOps automation, and Infrastructure as Code. Ability to create architecture blueprints, solution proposals, HLDs, LLDs, and transformation roadmaps. Desired Profile

Proven experience leading solutioning workshops, architecture assessments, and client-facing technical engagements. Strong consulting, stakeholder management, and technology advisory skills. Ability to define strategic data platform roadmaps aligned with business outcomes. Primary Focus Areas: Databricks Architecture | Solutioning | Lakehouse Design | Cloud Data Platforms | Spark Engineering | Data Modernization | Governance & Security | Performance Optimization | Pre-Sales & Technical Advisory.