Databricks Practice Lead Position Available In Fulton, Georgia
Tallo's Job Summary: The Databricks Practice Lead will own client engagement, aid in business development, and provide technical training on data engineering. Responsibilities include managing a team, leading sales calls, project management, and hands-on implementation of Databricks migration and infrastructure setup. They will collaborate globally to deliver innovative solutions to clients.
Job Description
The Databricks Practice Lead position will own client engagement, participate in the development of our practice, aid in business development, and contribute innovative ideas and initiatives to our company. They will work withthe Head of Data Engineering and Infrastructure and Aimpoint Digital Leadership and collaborate with a global team to deliver innovative solutions to our client base.
Day-to-day responsibilities include the following
- Provide technical training to internal and external staff on data engineering and Databricks
- Manage a team of junior and senior Data and ML Engineers
- Lead pre and post sales calls with C-suite executives and data leaders
- Responsible for project management and hands on implementation of all aspects of Databricks migration, infra setup, Autoloader and DLT E2E pipeline development, Unity Catalog and internal / external upskilling
- Migrate clients onto snowflake including data transformation and migration and E2E pipeline development using AWS, dbt, fivetran, Matillion, Astronomer / Airflow, streamlit and snowpark / snowflake functions, tasks and procedures
- Become a trusted advisor working together with our clients, from data owners and analytic users to C-level executives
- Engage and lead multi-disciplinary teams to solve complex use-cases across a variety of industries
- Assess existing analytics infrastructure and business processes and advise on best-in-class modern solutions
- Design and develop the analytical layer, building cloud data warehouses, data lakes, ETL/ELT pipelines, and orchestration tools
- Work with modern tools such as Snowflake, Databricks, Fivetran, and dbt
- Write code in SQL, Python, and Spark, and use software engineering best-practices such as Git and CI/CD
- Support the deployment of data science and ML projects into production.
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Note:
This position does not develop machine learning models or algorithms.)