Job
Description
Band 4c & 4D Skill set -Unity Catalog + Python , Spark , Kafka Inviting applications for the role of Lead Consultant- Databricks Developer with experience in Unity Catalog + Python , Spark , Kafka for ETL! In this role, the Databricks Developer is responsible for solving the real world cutting edge problem to meet both functional and non-functional requirements. Responsibilities Develop and maintain scalable ETL pipelines using Databricks with a focus on Unity Catalog for data asset management. Implement data processing frameworks using Apache Spark for large-scale data transformation and aggregation. Integrate real-time data streams using Apache Kafka and Databricks to enable near real-time data processing. Develop data workflows and orchestrate data pipelines using Databricks Workflows or other orchestration tools. Design and enforce data governance policies, access controls, and security protocols within Unity Catalog. Monitor data pipeline performance, troubleshoot issues, and implement optimizations for scalability and efficiency. Write efficient Python scripts for data extraction, transformation, and loading. Collaborate with data scientists and analysts to deliver data solutions that meet business requirements. Maintain data documentation, including data dictionaries, data lineage, and data governance frameworks. Qualifications we seek in you! Minimum qualifications Bachelors degree in Computer Science, Data Engineering, or a related field. experience in data engineering with a focus on Databricks development. Proven expertise in Databricks, Unity Catalog, and data lake management. Strong programming skills in Python for data processing and automation. Experience with Apache Spark for distributed data processing and optimization. Hands-on experience with Apache Kafka for data streaming and event processing. Proficiency in SQL for data querying and transformation. Strong understanding of data governance, data security, and data quality frameworks. Excellent communication skills and the ability to work in a cross-functional environ Must have experience in Data Engineering domain . Must have implemented at least 2 project end-to-end in Databricks. Must have at least experience on databricks which consists of various components as below Delta lake dbConnect db API 2.0 Databricks workflows orchestration Must be well versed with Databricks Lakehouse concept and its implementation in enterprise environments. Must have good understanding to create complex data pipeline Must have good knowledge of Data structure & algorithms. Must be strong in SQL and sprak-sql. Must have strong performance optimization skills to improve efficiency and reduce cost. Must have worked on both Batch and streaming data pipeline. Must have extensive knowledge of Spark and Hive data processing framework. Must have worked on any cloud (Azure, AWS, GCP) and most common services like ADLS/S3, ADF/Lambda, CosmosDB/DynamoDB, ASB/SQS, Cloud databases. Must be strong in writing unit test case and integration test Must have strong communication skills and have worked on the team of size 5 plus Must have great attitude towards learning new skills and upskilling the existing skills. Preferred Qualifications Good to have Unity catalog and basic governance knowledge. Good to have Databricks SQL Endpoint understanding. Good To have CI/CD experience to build the pipeline for Databricks jobs. Good to have if worked on migration project to build Unified data platform. Good to have knowledge of DBT. Good to have knowledge of docker and Kubernetes.
