Offer summary

Qualifications:

Minimum 5 years of experience with Databricks, including platform architecture and data engineering., Proficiency in Python, Scala, or Java, with experience in Spark and Delta Lake., Strong background in data warehousing, ETL processes, and data governance., Leadership skills with experience mentoring teams and driving technical initiatives..

Key responsibilities:

Design and implement scalable Databricks solutions to meet client needs.

Develop data pipelines, data lakes, and data warehousing solutions using Databricks.

Collaborate with data scientists and analysts to deploy machine learning models and analytics.

Optimize cluster performance and ensure data security and compliance.

Job description

Job Title: Data Architect – Databricks
Company: V4C.ai
Type: Full-time
Experience Level: Senior

We're seeking a skilled Data Architect with hands-on Databricks experience to help build robust pipelines and support scalable analytics and machine learning initiatives.

Key Responsibilities

Databricks Solution Architecture: Design and implement scalable, secure, and efficient Databricks solutions that meet client requirements.
Data Engineering: Develop data pipelines, architect data lakes, and implement data warehousing solutions using Databricks.
Data Analytics: Collaborate with data scientists and analysts to develop and deploy machine learning models and analytics solutions on Databricks.
Performance Optimization: Optimize Databricks cluster performance, ensuring efficient resource utilization and cost-effectiveness.
Security and Governance: Implement Databricks security features, ensure data governance, and maintain compliance with industry regulations.
Client Engagement: Work closely with clients to understand their business requirements, provide technical guidance, and deliver high-quality Databricks solutions.
Thought Leadership: Stay up to date with the latest Databricks features, best practices, and industry trends, and share knowledge with the team.

Requirements

Databricks Experience: 5+ years of experience working with Databricks, including platform architecture, data engineering, and data analytics.
Technical Skills: Proficiency in languages such as Python, Scala, or Java, and experience with Databricks APIs, Spark, and Delta Lake.
Data Engineering: Strong background in data engineering, including data warehousing, ETL, and data governance.
Leadership: Proven experience leading technical teams, mentoring junior engineers, and driving technical initiatives.
Communication: Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal stakeholders.

Good to Have

Certifications: Databricks Certified Professional or similar certifications.
Cloud Experience: Experience working with cloud platforms such as AWS, Azure, or GCP.
Machine Learning: Knowledge of machine learning concepts and experience with popular ML libraries