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Data Engineer
3 weeks ago
- Lead the design, development, and optimization of highly scalable, low-latency streaming and batch data pipelines.
- Engineer real-time data solutions using technologies such as Apache Kafka, Apache Flink, and Spark Streaming.
- Collaborate closely with product, analytics, AI/ML, and platform teams to ensure data is treated as a first-class, strategic asset.
- Drive platform modernization initiatives including cloud-native services and streaming-first design patterns.
- Establish and enforce best practices for data governance, security, performance tuning, and operational reliability.
- Implement end-to-end observability for data pipelines, including defining metrics and establishing SLAs.
- 10+ years of professional experience in software or data engineering, with 4+ years focused on streaming and real-time data systems.
- Deep expertise in streaming technologies such as Apache Kafka, Flink, and Spark Streaming.
- Hands-on experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments for data workloads.
- Proven experience implementing data quality frameworks and CI/CD integrations.
- Strong foundation in event-driven architectures, distributed systems, and resilient low-latency pipelines.
- Operational excellence in observability, including metrics, logging, and alerting for data pipelines.
- Make an impact at one of the world's fastest-growing AI-first digital engineering companies.
- Upskill and discover your potential as you solve complex challenges in cutting-edge technology.
- Work where innovation happens with disruptive innovators in a research-focused organization.
- Gain exposure working with Fortune 500 companies and immerse yourself in breakthrough technologies.