Databricks Solution Architect

EXL

. Define the enterprise data architecture on Databricks, including ingestion, medallion layering, serving, ML and source-system integration .

Posted 11/11/2026full-timeSan Francisco • California • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in defining enterprise data architecture on Databricks, including ingestion, medallion layering, and compliance. Proficient in stakeholder management, vendor evaluations, and designing secure platforms for PII/NPI protection.

Highest-signal resume keywords

Databricks Lakehouse PlatformStrong SparkData Modeling ExperienceAWS Architecture ExperienceFinOps and Cost Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDelta LakeBatch and Streaming DesignKafkaStructured StreamingDisaster Recovery DesignHigh-Availability DesignMigration PlanningMedallion ModelingDimensional Modeling

Soft Skills

Stakeholder ManagementVendor ManagementClear Architecture Documentation

Tools & Technologies

HadoopHiveEMRUnity CatalogEncryptionAudit LoggingLineage

Certifications & Qualifications

Databricks Solution ArchitectAWS Solution Architect

Industry Keywords

BankingLendingRegulated Financial ServicesMarketing Data ArchitectureCollections Data ArchitectureML/MLOps Architecture

Tech Stack

Tools & technologies

AWSCloudHadoopKafkaSparkSQLUnity

About the role

Key responsibilities & impact

Define the enterprise data architecture on Databricks, including ingestion, medallion layering, serving, ML and source-system integration
Run discovery with business and technology stakeholders
Turn requirements into solution designs, reference architectures and delivery roadmaps
Design marketing architecture for identity resolution, segmentation, campaign measurement, attribution and compliant data sharing
Design collections architecture for near-real-time delinquency and contact data, vendor exchange, contact preferences and regulatory restrictions
Make batch-versus-streaming, build-versus-buy, workspace topology, network, multi-account and disaster-recovery decisions
Design security and compliance architecture with InfoSec, including Unity Catalog, PII/NPI protection, encryption, audit logging and lineage
Plan and sequence migration from legacy Hadoop/Hive/EMR and warehouse workloads
Build DBU forecasting, FinOps guardrails, cost and capacity models, and business cases for platform investments
Chair the architecture review board and maintain standards, reference patterns and decision records
Manage Databricks and cloud-provider relationships and lead vendor evaluations and proofs of concept
Own target-state architecture, cross-domain decisions, vendor relationships and cost modeling while partnering with the Principal Engineer on detailed designs and pipelines

Requirements

What you’ll need

12+ years in data engineering or architecture
5+ years on the Databricks lakehouse platform
Strong Spark, Delta Lake and SQL
Data modeling experience, including medallion and dimensional modeling
AWS architecture experience with networking, IAM, encryption and multi-account design
Secure platform design for PII/NPI, including Unity Catalog access models and lineage
Migration planning from legacy Hadoop, Hive and warehouse systems
Batch and streaming design experience, including Kafka and Structured Streaming
Disaster recovery and high-availability design experience
FinOps and Databricks cost and capacity modeling, including business-case development
Stakeholder management, vendor management and clear architecture documentation
Graduate in Computer Science, Data Science, or a related field
Banking, lending or regulated financial services experience preferred
Marketing data architecture experience preferred
Collections data architecture experience preferred
ML/MLOps architecture on Databricks preferred
Databricks and AWS Solution Architect certifications preferred

Benefits

Comp & perks

Hybrid work arrangement
Opportunity to work on a modern Databricks data platform
Collaboration with the Principal Engineer and cross-functional stakeholders
Professional and architectural leadership opportunities
Exposure to Databricks account team and cloud provider relationships