Data engineers with Kafka

Job description andidate must have an agile mindset; An expert in Scaled Agile delivery model, experienced with agile ceremonies such as daily scrums, spring planning, sprint reviews and sprint demos. Design and implement low-latency, high-throughput streaming pipelines using Kafka, Flink, and Spark Streaming. Build and maintain event-driven architectures for real-time data ingestion and processing. Develop stateful and stateless stream processing applications using Flink and Spark Structured Streaming. Collaborate closely with various application teams to define integration points and API specification. Report progress, test metrics and results to the project stakeholders. Perform all activities involved in the software testing lifecycle. Highly effective written and verbal communication skills Required Qualifications: Candidate must have an agile mindset; An expert in Scaled Agile delivery model, experienced with agile ceremonies such as daily scrums, spring planning, sprint reviews and sprint demos. Should have 6+ years of hands-on experience in data engineering roles Strong experience in building streaming pipeline Hands-on expertise with Hadoop ecosystem, Kafka, Flink, Spark Streaming and SQL Scala and Python Oracle Database, SQL, PL/SQL. Familiarity with CI/CD tools (Git, Bitbucket, uDeploy, ServiceNow) Preferred Qualifications: Experience in building enterprise-scale data platforms Exposure to cloud-based data ecosystems (AWS, Azure, or GCP) Knowledge of data governance, security, and compliance practices Experience mentoring junior team members Role: Other Industry Type: IT Services & Consulting Department: Other Employment Type: Full Time, Permanent Role Category: Other Education UG: Any Graduate Key Skills Skills highlighted with ‘‘ are preferred keyskills ScalaData engineerKafkaFlinkPython