Data Bricks Practice Architect

TEKsystems•Austin, TX

3d•$148,200 - $222,400•Remote

About The Position

Think of TEKsystems Global Services (TGS) as the growth solution for enterprises today. We unleash growth through technology, strategy, design, execution and operations with a customer-first mindset for bold business leaders. We deliver cloud, data and customer experience solutions. Our partnerships with leading cloud, design and business intelligence platforms fuel our expertise. We value deep relationships, dedication to serving others and inclusion. We drive positive outcomes for our people and our business, and we stay true to our commitments and act in harmony with our words. We exist to create significant opportunity for people to achieve fulfillment through career success. Ready to join us? Here’s what the opportunity supported through our TGS Talent Acquisition Team requires: Join our Data Modernization and Gen AI practice and take the lead across designing, building, and maintaining data pipelines and analytics solutions on the Databricks cloud platform and collaborate with data analysts and customer stakeholders to ensure the availability, scalability, and reliability of data. The Individual • Consultative and personable data engineering leader who will provide advice and leading expertise on Databricks and have a deep understanding of cloud data services to become a key contributor to various large scale data projects. • Works on specific projects critical to our needs with opportunities to switch teams and projects as our fast-paced business grows and evolves. • Is versatile, displays leadership qualities and is enthusiastic to take on new challenges across the data stack. Qualifications Minimum qualifications: • Bachelor’s or higher degree in Computer Science, Information Technology, or a related field. • 10+ years industry experience building and supporting large-scale cloud systems. • Ability to speak and write in English fluently. • Excellent verbal and written communication skills.

Requirements

Experience with Databricks, Spark and working knowledge of DBT for data processing and transformation.
Working understanding of Data Warehousing concepts of Data Vault, Dimensional modelling, OLAP design.
Hands-on experience building data pipelines using technology such as Azure Data Factory, AWS Glue, GCP Dataflow and Apache Spark (preferably in Databricks).
Extensive experience with CI/CD platforms such as GitLab CI, GitHub Actions, AWS CodeBuild, Azure Pipelines, GCP Cloud Build, and Jenkins.
Skilled in scripting languages including Python, SQL, R, Scala, Bash, and PowerShell.
Familiarity with log and monitoring solutions.
Experience in utilizing development containers, unit testing/code quality review - standard best practices.
Proficiency in Python and SQL for data transformation and querying.
Strong expertise in version control systems.
Familiarity with containerization and orchestration technologies.
Strong problem-solving, troubleshooting, communication and collaboration skills.
Familiarity with Generative AI Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and Agentic AI techniques.

Nice To Haves

Professional Certification in one or more areas: Cloud Architecture, Data Engineering, Data Analyst, ML Engineer
Databricks certified candidates will be preferred.

Responsibilities

Design & Architecture: Design and implement solutions for the Databricks platform and APIs. Work with data engineering and data science teams, customers, and other customer-facing teams.
Technical leadership: Provide technical guidance to customers on big data projects, including architectural design, data engineering, and model deployment
Customer collaboration: Work with customers to understand their requirements, and help them define solutions and a roadmap to meet their goals
Solution design: Create and review architecture and solution design artifacts
Technical expertise: Demonstrate expertise in Databricks Lakehouse architecture, delta lake medallion architecture, data pipelines, CI/CD pipelines etc.
Communication: Communicate complex technical concepts to non-technical stakeholders, such as business leaders and C-level executives
Documentation: Develop and maintain documentation for the Databricks platform, such as deployment guides, operational procedures, and architecture diagrams
Risk management: Identify, communicate, and mitigate risks, assumptions, issues, and decisions.