Data Engineer

• Design and develop real-time data streaming pipelines with Apache Kafka, Flume, and Apache Storm for event-driven applications.
• Ensure high availability and fault tolerance through scalable systems using YARN, Kubernetes, Docker, and Redis for checkpointing.
• Develop and optimize Spark applications in Scala, processing large datasets and integrating XML data parsing (DOM/SAX).
• Model and implement scalable Cassandra solutions, focusing on high-throughput, low-latency real- time data storage and queries.
• Integrate Cassandra with Spark, Kafka, and Flume for real-time data ingestion and analytics.
• Design and implement cloud-based deployments on AWS, leveraging services like EC2, S3, and Redshift.
• Automate cloud infrastructure provisioning using AWS CloudFormation, Terraform, and Ansible for scalable and reproducible environments.
• Implement monitoring and alerting systems using Splunk, Grafana, Elastic Search on AWS for system health tracking.
• Develop and maintain backend applications using Java, Scala, Spring Boot, and Akka for scalable microservices.
• Optimize backend services for performance, reliability, and scalability in a microservices architecture.
• Ensure data security and compliance by implementing encryption, access control, and other best practices across data storage, pipelines, and cloud infrastructure.
• Design and optimize Cassandra data models for time-series data, ensuring efficient queries and minimal latency.
• Write high-performance data pipelines for real-time data processing, using technologies such as Kafka and Spark Streaming.
• Work on system performance optimization, including fine-tuning Spark jobs, Cassandra clusters, and Kafka-based pipelines for optimal throughput.
• Develop and expose RESTful APIs and GraphQL endpoints for backend services to interact with external systems or clients.
• Collaborate with stakeholders to translate business requirements into technical solutions, ensuring high-quality project delivery.
• Contribute to product roadmaps, prioritize features, and align development efforts with business goals.
• Lead and mentor junior engineers, providing guidance on best practices for system design, code quality, and performance tuning.
• Manage client expectations and ensure smooth project execution through regular status updates, reviews, and collaboration.
• Drive project delivery by managing timelines, effort estimation, work breakdown, and ensuring alignment with business objectives.

Technologies/Environment involved:

• Big Data / Hadoop: HDFS, MapReduce, Apache Pig, Hive, Sqoop, Flume, Yarn (MR2), Impala, Zookeeper, HUE (Hadoop User Experience), Sentry, Oozie, Spark, Key Management Server, Shell Scripting, Cloud Computing Architecture.
• Data Visualization and BI Tools: ETL Process Tools , Dashboard , Data Analytics, Tableau.
• Operating Systems: Linux, Unix, Windows.
• Databases: MongoDB, DynamoDB, Postgres, MySQL, Oracle.
• Cloud Technologies: WCNP, AWS, Azure.
• DevOps Tools: GitHub, Gradle, Jenkins, Docker, Kubernetes.
• Programming Languages & Framework: Java, Scala, Python, Spring, Akka, Flask
• Log monitoring tools: Datadog, Splunk, Grafana, Cloud watch

Do you have experience in ZooKeeper?, Do you have a Master’s degree?, Data Engineer with Bachelor’s degree in Computer Science, Computer Information Systems, Information Technology, or a combination of education and experience equating to the U.S. equivalent of a Master’s degree in one of the aforementioned subjects.