Data Engineer

Job Description : Mid-Level Data Engineer with Databricks Certification (Advanced Data Engineer Certification or Equivalent Fabric Certification) to design and optimize data solutions that drive business insights and innovation. The ideal candidate will have experience in data engineering, an understanding of machine learning workflows, and knowledge of modern data architectures.

Responsibilities :

Design, develop, and maintain scalable data pipelines and workflows using Databricks.

Integrate and process structured and unstructured data using Delta Live Tables, Streaming Data Processing.

Support and optimize machine learning workflows by preparing and managing training and inference datasets.

Collaborate with data scientists and AI teams to support AI / BI Genie integrations.

Implement Snowflake and Star Schema architectures to optimize data storage and query performance.

Work on BI reporting pipelines to ensure compatibility with advanced analytics tools.

Develop and maintain documentation of data processes and architectures.

Optimize Spark jobs and workflows for performance and cost-efficiency.

Troubleshoot and resolve data quality and pipeline issues.

Stay updated on advancements in data engineering, machine learning, and AI technologies.

Requirements :

Databricks Certification (e.g., Databricks Certified Professional Data Engineer).

3-7 years of experience in data engineering roles.

Proficiency in Python, SQL, and Apache Spark.

Hands-on experience with Delta Live Tables and big data processing frameworks.

Understanding machine learning models, pipelines, and AI tools.

Familiarity with AI / BI Genie or similar tools for business intelligence.

Experience with Data Warehouse Architecture (e.g., Snowflake, Star Schema, Kimball methodology).

Knowledge of cloud platforms like AWS, Azure, or GCP.

Strong problem-solving skills and ability to work in a collaborative environment.