This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking a highly experienced Solutions Architect to lead the design and delivery of end-to-end data and analytics solutions on the Databricks platform. You will translate complex business needs into scalable, secure, and cost-efficient data lakehouse architectures, collaborate with cross-functional teams, and guide customers from concept through implementation and adoption.
Job Responsibility
Engage with business stakeholders to understand goals, data sources, and analytic use cases
translate into a holistic Databricks-based solution
Design scalable data lakehouse architectures on Databricks (Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables) that support data ingestion, cleansing, modeling, governance, security, and analytics
Lead technical architecture decisions and produce high-quality artifacts (reference architectures, solution blueprints, data models, data governance models, and integration plans)
Architect data pipelines end-to-end (ingestion, transformation, storage, cataloging) with best practices for reliability, observability, and cost optimization
Enable data science and ML workflows on Databricks (MLflow, feature store, notebooks, Automated ML) and design end-to-end MLOps strategies
Ensure data governance, security, and compliance (IAM, encryption, Unity Catalog, data masking, lineage, access controls)
Collaborate closely with data engineers, data scientists, software engineers, and DevOps to deliver production-ready solutions
implement CI/CD for data and ML pipelines
Lead customer-facing activities: workshops, solution demos, proofs of concept, and responses to RFPs/RFIs
provide strategic guidance on platform adoption and ROI
Mentor and coach junior architects and engineers
develop training materials and run knowledge-sharing sessions
Monitor performance, optimize SQL and Spark workloads, manage cluster configurations, and drive cost/performance improvements
Requirements
8+ years of experience in solutions/enterprise architecture or senior data engineering roles
3+ years of hands-on experience with the Databricks platform and Spark-based architectures
Deep expertise in Databricks components: Delta Lake, Unity Catalog, Databricks SQL, Delta Live Tables, notebooks, and orchestration patterns
Strong cloud experience (AWS, Azure, or GCP) with data storage and compute services (e.g., S3/Blob, ADLS, GCS, Redshift, BigQuery, Synapse, EMR/Databricks on cloud)
Proficiency in data integration and orchestration tools (e.g., Apache Airflow, dbt, Kafka, Spark Structured Streaming)
Advanced SQL and programming skills (Python or Scala)
ability to prototype and review data pipelines, models, and analytics solutions
Excellent communication and stakeholder management skills
ability to present complex technical concepts to both technical and non-technical audiences
Experience delivering large-scale data lakehouse migrations/transformations, performance tuning, and cost optimization
Databricks certification(s) or equivalent demonstrable expertise
willingness to obtain relevant certifications if not already held
Nice to have
Experience with ML and MLOps on Databricks (MLflow, feature stores, model registry, CI/CD for ML)
Domain expertise in industries such as financial services, healthcare, retail, or telecommunications
Familiarity with data governance, privacy regulations, and security frameworks (e.g., GDPR, HIPAA, SOC 2)
Familiarity with real-time data processing and streaming architectures
Prior experience in pre-sales or solutioning for customers, including building compelling ROI stories and technical demos