Job
Description
About Us: Celebal Technologies is a leading Solution Service company that provide Services the field of Data Science, Big Data, Enterprise Cloud & Automation. We are at the forefront of leveraging cutting-edge technologies to drive innovation and enhance our business processes. As part of our commitment to staying ahead in the industry, we are seeking a talented and experienced Data & AI Engineer with strong Azure cloud competencies to join our dynamic team. Job Summary: We are looking for a highly skilled Azure Data Engineer with a strong background in real-time and batch data ingestion and big data processing, particularly using Kafka and Databricks . The ideal candidate will have a deep understanding of streaming architectures , Medallion data models , and performance optimization techniques in cloud environments. This role requires hands-on technical expertise , including live coding during the interview process. Key Responsibilities Design and implement streaming data pipelines integrating Kafka with Databricks using Structured Streaming . Architect and maintain Medallion Architecture with well-defined Bronze, Silver, and Gold layers . Implement efficient ingestion using Databricks Autoloader for high-throughput data loads. Work with large volumes of structured and unstructured data , ensuring high availability and performance. Apply performance tuning techniques such as partitioning, caching , and cluster resource optimization . Collaborate with cross-functional teams (data scientists, analysts, business users) to build robust data solutions. Establish best practices for code versioning , deployment automation , and data governance . Required Technical Skills: Strong expertise in Azure Databricks and Spark Structured Streaming Processing modes (append, update, complete) Output modes (append, complete, update) Checkpointing and state management Experience with Kafka integration for real-time data pipelines Deep understanding of Medallion Architecture Proficiency with Databricks Autoloader and schema evolution Deep understanding of Unity Catalog and Foreign catalog Strong knowledge of Spark SQL, Delta Lake, and DataFrames Expertise in performance tuning (query optimization, cluster configuration, caching strategies) Must have Data management strategies Excellent with Governance and Access management Strong with Data modelling, Data warehousing concepts, Databricks as a platform Solid understanding of Window functions Proven experience in: Merge/Upsert logic Implementing SCD Type 1 and Type 2 Handling CDC (Change Data Capture) scenarios Retail/Telcom/Energy any one industry expertise Real time use case execution Data modelling
