AWS Databricks Architect

NXT GIG is in search of a skilled AWS Databricks Architect to join our innovative team and lead the design and deployment of big data solutions using Databricks on AWS. In this role, you will be responsible for architecting and implementing robust data processing and analytics workflows that leverage the capabilities of the AWS cloud and Databricks platform. You will collaborate closely with cross-functional teams to identify data requirements, optimize data pipelines, and ensure the efficient transformation and analysis of large datasets. The ideal candidate will have extensive experience with cloud data architectures, data engineering practices, and the Databricks environment. If you are passionate about big data and cloud technologies, we encourage you to apply and play a critical role in advancing our data initiatives at NXT GIG.

Responsibilities

• Design and implement scalable and efficient data architectures using AWS services and Databricks.
• Collaborate with data scientists, data engineers, and business stakeholders to identify data processing needs and requirements.
• Develop and optimize ETL processes to ensure high-quality data ingestion and transformation.
• Establish best practices for data governance, security, and compliance within the Databricks environment.
• Monitor and troubleshoot data processing workflows to ensure reliability and performance.
• Stay current with emerging trends and technologies in big data and AWS services relevant to Databricks.
• Provide technical mentorship to team members and support knowledge sharing within the organization.

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.
• Proven experience as an AWS Databricks Architect or in a similar role focused on big data solutions.
• Strong expertise in AWS services, particularly those related to data processing and storage (e.g., S3, Redshift, Glue).
• In-depth knowledge of Databricks, Apache Spark, and related big data technologies.
• Experience with data modeling, ETL processes, and data pipeline optimization.
• Excellent analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
• Strong communication and collaboration skills to work effectively with cross-functional teams.