Job SummaryWe are looking for a highly skilled
Databricks Solution Architect to lead the design and implementation of scalable, enterprise-grade data platforms using Databricks. The ideal candidate will combine strong technical expertise in data engineering and cloud platforms (AWS, Azure, or GCP) with architectural leadership, solution design capability, and strong stakeholder engagement skills.
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Primary SkillsDatabricks, AWS, SQL
Cloud PlatformsAWS, Azure, GCP
Mandatory Skills- Senior Databricks Engineer
- AWS
- SQL
Key ResponsibilitiesSolution Architecture & Design- Design end-to-end data architectures using the Databricks Lakehouse Platform.
- Architect scalable ETL/ELT pipelines, real-time streaming solutions, and advanced analytics platforms.
- Define data models, storage strategies, and integration patterns aligned with business and enterprise architecture standards.
- Provide guidance on cluster configuration, performance optimization, cost management, and workspace governance.
Technical Leadership- Lead technical discussions and design workshops with engineering teams and business stakeholders.
- Provide best practices, frameworks, and reusable component designs for consistent delivery.
- Perform code reviews and provide technical mentoring to data engineers and developers.
Stakeholder & Project Engagement- Collaborate with product owners, business leaders, and analytics teams to translate business requirements into scalable technical solutions.
- Create and present solution proposals, architectural diagrams, and implementation strategies.
- Support pre-sales or discovery phases with technical input when needed.
Data Governance, Security & Compliance- Define and implement governance standards across Databricks workspaces, including data lineage, cataloging, and access control.
- Ensure compliance with regulatory and organizational security frameworks.
- Implement best practices for monitoring, auditing, and data quality management.
Continuous Improvement & Innovation- Stay updated on Databricks features, roadmap, and industry trends.
- Recommend improvements, optimizations, and modernization opportunities across the data ecosystem.
- Evaluate the integration of complementary technologies, including Delta Live Tables, MLflow, Unity Catalog, and streaming frameworks.
Required Skills & ExperienceDatabricks- Strong hands-on experience with Databricks, including:
- Clusters
- Notebooks
- Delta Lake
- MLflow
- Unity Catalog
Cloud Platforms- Experience with at least one cloud provider:
- AWS
- Azure
- GCP
Data Engineering- Strong proficiency in:
- Apache Spark
- Python
- SQL
- Distributed data processing
Data Architecture- Experience designing large-scale data solutions, including:
- Data ingestion
- Data transformation
- Data storage
- Analytics platforms
Streaming Technologies- Experience with:
- Structured Streaming
- Apache Kafka
- Amazon Kinesis
- Azure Event Hub
DevOps- Experience with CI/CD practices for data pipelines using:
- Azure DevOps
- GitHub Actions
- Jenkins
Soft Skills- Strong communication skills with the ability to engage both technical and business teams.
- Experience working in Agile environments.
- Ability to simplify complex technical concepts for non-technical audiences.
- Strong analytical, problem-solving, and decision-making abilities.
Preferred Qualifications- Databricks Certified Data Engineer Professional or Architect Certification.
- AWS, Azure, or GCP Cloud Architect Certifications.
- Experience with BI tools such as Tableau, Power BI, or Looker.
- Experience with Machine Learning workflows and MLOps.
Background in large-scale data modernization or cloud migration projects
