Confluent Kafka

Job Title: Data Engineer - Ingestion, Storage & Streaming (Confluent Kafka)

Job Summary:

As a Data Engineer specializing in Ingestion, Storage, and Streaming, you will design, implement, and maintain robust, scalable, and high-performance data pipelines for the efficient flow of data through our systems. You will work with Confluent Kafka to build real-time data streaming platforms, ensuring high availability and fault tolerance. You will also ensure that data is ingested, stored, and processed efficiently and in real-time to provide immediate insights.

Key Responsibilities:

• Kafka-Based Streaming Solutions:
• Design, implement, and manage scalable and fault-tolerant data streaming platforms using Confluent Kafka.
• Develop real-time data streaming applications to support business-critical processes.
• Implement Kafka producers and consumers for ingesting data from various sources.
• Handle message brokering, processing, and event streaming within the platform.
• Ingestion & Data Integration:
• Build efficient data ingestion pipelines to bring real-time and batch data from various data sources into Kafka.
• Ensure smooth data integration across Kafka topics and handle multi-source data feeds.
• Develop and optimize connectors for data ingestion from diverse systems (e.g., databases, external APIs, cloud storage).
• Data Storage and Management:
• Manage and optimize data storage solutions in conjunction with Kafka, including topics, partitions, retention policies, and data compression.
• Work with distributed storage technologies to store large volumes of structured and unstructured data, ensuring accessibility and compliance.
• Implement strategies for schema management, data versioning, and data governance.
• Data Streaming & Processing:
• Leverage Kafka Streams and other stream processing frameworks (e.g., Apache Flink, ksqlDB) to process real-time data and provide immediate analytics.
• Build and optimize data processing pipelines to transform, filter, aggregate, and enrich streaming data.
• Monitoring, Optimization, and Security:
• Set up and manage monitoring tools to track the performance of Kafka clusters, ingestion, and streaming pipelines.
• Troubleshoot and resolve issues related to data flows, latency, and failures.
• Ensure data security and compliance by enforcing appropriate data access policies and encryption techniques.
• Collaboration and Documentation:
• Collaborate with data scientists, analysts, and other engineers to align data systems with business objectives.
• Document streaming architecture, pipeline workflows, and data governance processes to ensure system reliability and scalability.
• Provide regular updates on streaming and data ingestion pipeline performance and improvements to stakeholders.

Required Skills & Qualifications:

• Experience:
• 3+ years of experience in data engineering, with a strong focus on Kafka, data streaming, ingestion, and storage solutions.
• Hands-on experience with Confluent Kafka, Kafka Streams, and related Kafka ecosystem tools.
• Experience with stream processing and real-time analytics frameworks (e.g., ksqlDB, Apache Flink).
• Technical Skills:
• Expertise in Kafka Connect, Kafka Streams, and Kafka producer/consumer APIs.
• Proficient in data ingestion and integration techniques from diverse sources (databases, APIs, etc.).
• Strong knowledge of cloud data storage and distributed systems.
• Experience with programming languages like Java, Scala, or Python for Kafka integration and stream processing.
• Familiarity with tools such as Apache Spark, Flink, Hadoop, or other data processing frameworks.
• Experience with containerization and orchestration tools such as Docker, Kubernetes.