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Tech Stack
Tools & technologiesApacheCloudGradleJavaKafkaMavenMicroservicesPythonScalaSpark
About the role
Key responsibilities & impact- Build and operate scalable batch and streaming data pipelines (e.g., Kafka, Spark), ensuring reliable ingestion, processing, and recovery in production environments.
- Design and implement data quality and governance mechanisms including validation, lineage, and monitoring to ensure trusted and accurate datasets.
- Develop observability and reliability tooling across data platforms using metrics, logs, traces, CI/CD, automated testing, alerting, and incident response.
- Contribute to robust and scalable data architecture, applying software engineering best practices, reusable components, and clean design principles.
- Collaborate with Product, Engineering, Analytics, and domain experts to translate requirements into scalable data solutions with measurable impact.
- Participate in Agile delivery processes, including planning, estimation, reviews, and retrospectives, contributing to predictable and iterative delivery.
- Continuously optimize performance, scalability, and cost efficiency across data pipelines, storage, and infrastructure.
- Ensure security, privacy, and compliance standards are embedded in all data handling and processing workflows.
Requirements
What you’ll need- Data-focused software engineering background with production experience with stateful, large‑scale data systems.
- Experience with streaming technologies such as Apache Kafka, Kafka Streams, and Apache Flink, as well as Avro and stateful data processing.
- Programming experience in Java, Scala, Python, or similar (language flexible)
- Strong understanding of distributed, event‑driven architectures
- Strong debugging and performance optimization skills in data-intensive systems
- Ownership, accountability, and a proactive, execution-focused mindset with strong pragmatic problem-solving.
- Cross-functional collaboration with clear, structured communication, especially in ambiguous or fast-moving environments.
- Data‑pipeline orchestration and workflow management
- Cloud infrastructure & infrastructure‑as‑code
- Containerized microservices environments
- JVM build‑system tuning (Gradle/Maven)
Benefits
Comp & perks- We are accessible and supportive to colleagues and clients with a friendly approach.
ATS Keywords
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Hard Skills & Tools
data pipelinesstreaming datadata qualitydata governanceobservabilityreliability toolingAgile deliveryperformance optimizationprogramming in Javaprogramming in Scala
Soft Skills
ownershipaccountabilityproactive mindsetproblem-solvingcross-functional collaborationstructured communication