Sr. Databricks Solutions Architect
Listed on 2026-06-24
-
IT/Tech
Data Engineering, Cloud Computing: Infrastructure & Operations, AI Engineer (Applied/Software)
Job Title: Sr. Databricks Solutions Architect
Location: Huntsville, Alabama (2 Days Hybrid)
Duration: Fulltime
Experience
Required:
10 – 15 Years
Lead customer engagements to design, build, and optimize Databricks-based architectures for advanced analytics, data engineering, and machine learning workloads.
Develop scalable ETL/ELT pipelines and integrate with cloud platforms (AWS, Azure, or GCP).
Guide customers on data governance, security, and compliance best practices within Databricks environments.
Consult on architecture, reference implementations, and best practices for leveraging Delta Lake, Unity Catalog, MLflow, and related Databricks capabilities.
Assist customers with productionalizing data pipelines, machine learning workflows, and AI-driven applications.
Provide escalated technical support for customer operational issues and help troubleshoot complex platform or workflow challenges.
Collaborate with internal and Databricks teams, including Engineers, Architects, Project Managers, and Customer Success teams, to ensure engagement goals are met.
Document technical designs, architecture patterns, deployment procedures, and lessons learned.
Stay current on Databricks platform features, distributed computing trends, and emerging big data technologies.
Deliver solutions that improve performance, scalability, and operational efficiency while meeting customer business objectives.
Support Professional Services and Managed Services initiatives as needed, ensuring billable deliverables meet customer expectations.
Required Skills- US Secret Clearance required. (Secret)
- 7+ years of experience in Data Engineering.
- 10+ years of consulting experience, preferably in data platform or analytics-focused engagements.
- Completion of 6–8 hands‑on projects with Databricks in production environments.
- Proven experience with Databricks, including Spark, Delta Lake, MLflow, and cloud integration.
- Strong proficiency in Python and/or SQL for data engineering and analytics.
- Deep understanding of distributed computing concepts and Apache Spark runtime internals.
- Hands‑on experience designing and deploying end‑to‑end big data and machine learning solutions.
- Familiarity with data modeling, performance tuning, and production‑grade pipeline design.
- Experience working directly with customers in a consulting or professional services capacity.
- Ability to manage technical scope, timelines, and delivery while maintaining excellent customer communication.
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent professional experience.
- Willingness to travel up to 30% for customer engagements.
- Master’s or PhD in Computer Science, Data Science, or related field.
- Experience implementing MLOps pipelines and product ionizing machine learning workflows.
- Knowledge of CI/CD, version control (Git), and infrastructure-as-code tools (Terraform, ARM, Cloud Formation).
- Exposure to streaming data technologies (Kafka, Kinesis, Event Hubs).
- Familiarity with data visualization tools (Tableau, Power BI, Looker).
- Experience with regulatory compliance frameworks (HIPAA, FedRAMP, SOC2).
- Prior consulting experience with technical project delivery in enterprise environments.
- Strong documentation, whiteboarding, and customer presentation skills.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).