Kafka Data Engineer

Kafka Data EngineerData Engineer to build and manage data pipelines that support batch and streaming data solutions. The role requires expertise in creating seamless data flows across platforms like Data Lake/Lakehouse in Cloudera, Azure Databricks, Kafka for both batch and stream data pipelines etc.ResponsibilitiesStrong experience in develop, test, and maintain data pipelines (batch & stream) using Cloudera, Spark, Kafka and Azure services like ADF, Cosmos DB, Databricks, NoSQL DB/ Mongo DB etc.Strong programming skills in spark, python or scala & SQL.Optimize data pipelines to improve speed, performance, and reliability, ensuring that data is available for data consumers as required.Create ETL pipelines for downstream consumers by transform data as per business logic.Work closely with Data Architects and Data Analysts to align data solutions with business needs and ensure the accuracy and accessibility of data.Implement data validation checks and error handling processes to maintain high data quality and consistency across data pipelines.Strong analytical and problem solving skills, with a focus on optimizing data flows and addressing impacts in the data pipeline. Qualifications8+ years of IT experience with at least 5+ years in data engineering and cloud-based data platforms.Strong experience with Cloudera/any Data Lake, Confluent/Apache Kafka, and Azure Data Services (ADF, Databricks, Cosmos DB).Deep knowledge of NoSQL databases (Cosmos DB, MongoDB) and data modeling for performance and scalability.Proven expertise in designing and implementing batch and streaming data pipelines using Databricks, Spark, or Kafka.Experience in creating scalable, reliable, and high-performance data solutions with robust data governance policies.Strong collaboration skills to work with stakeholders, mentor junior Data Engineers, and translate business needs into actionable solutions.Bachelors or masters degree in computer science, IT, or a related field.