Sr. Databricks Solutions Architect

Everforth Ecs
Huntsville, AL, United States
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Data Analysis Microsoft Azure Big Data Information Systems Continuous Integration Information Engineering Data Governance Data Infrastructure Extract Transform Load (ETL) Data Visualization Distributed Systems
+25 more
Python (Programming Language) Machine Learning Performance Tuning Power BI SQL Databases Data Streaming Tableau (Software) Azure Service Bus Google Cloud Apache Spark Git Cloudformation Data Lakes Infrastructure Automation Frameworks Information Technology Data Analytics Apache Kafka Machine Learning Operations Virtual Agents Cloud Integration Terraform Looker Analytics Software Version Control Data Pipelines Databricks

Job description

Everforth ECS is seeking a Sr. Databricks Solutions Architect to join our team in Huntsville, Alabama . This position is contingent upon contract award.

ECS is seeking a skilled Sr. Databricks Solutions Architect to join our Professional Services team. This position is contingent upon contract award. If you are passionate about helping customers solve complex big data challenges, leveraging Databricks for advanced analytics, machine learning, and AI-driven insights, and enjoy working in a consulting environment where technical expertise meets client engagement, this role is for you.

As a member of our team, you will work with customers on short- to medium-term engagements, providing technical guidance, architecture, and hands-on support to ensure they maximize value from their Databricks environments. You will collaborate with clients to design, implement, and optimize data pipelines, analytics workflows, and machine learning solutions, all while delivering exceptional customer service and consulting expertise.

Responsibilities

  • 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 Google Cloud Platform).
  • 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.

Requirements

  • US Top Secret Clearance required.
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent professional experience.
  • 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.
  • Willingness to travel up to 30% for customer engagements.

Desired Skills

  • Master’s or PhD in Computer Science, Data Science, or related field.
  • Experience implementing MLOps pipelines and productionizing machine learning workflows.
  • Knowledge of CI/CD, version control (Git), and infrastructure-as-code tools (Terraform, ARM, CloudFormation).
  • 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.

About the company

Everforth ECS is the federal segment of Everforth , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies.

Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.dice.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

1:46 min

Traditional data architecture before Microsoft Fabric

Dr. Alexander Wachtel Dr. Alexander Wachtel +1 · WWC 2025

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

3:48 min

Standardizing data access schemas with OData

Florian Bader Florian Bader · WWC Europe 2026

Videos

See all

Related articles

See all