Company Overview: Welcome to the forefront of data-driven innovation! Our company is dedicated to harnessing the power of real-time data to drive transformative change and solve complex problems across industries. We're committed to building cutting-edge real-time data solutions that enable timely insights and actions. Join us and be part of a dynamic team shaping the future of real-time data engineering.
Position Overview: As a Senior Real-Time Data Engineer, you'll play a crucial role in designing, building, and optimizing our real-time data infrastructure. You'll work on challenging projects, from architecting data streaming pipelines to developing real-time analytics systems, to support the needs of our data-driven organization. If you're a seasoned engineer with expertise in real-time data technologies and a passion for building scalable and reliable systems, we want you on our team.
Key Responsibilities:
- Real-Time Data Architecture: Design and implement scalable and reliable architecture for real-time data processing and analytics, including data ingestion, processing, and serving layers.
- Streaming Data Pipelines: Develop and maintain real-time data streaming pipelines using technologies such as Apache Kafka, Apache Flink, or Apache Spark Streaming, ensuring low-latency and high-throughput data processing.
- Event-Driven Architecture: Design event-driven systems to enable real-time processing of data events and triggers, supporting use cases such as real-time monitoring, anomaly detection, and alerting.
- Data Integration: Integrate real-time data streams from diverse sources and systems into the real-time data infrastructure, ensuring data consistency, integrity, and quality.
- Real-Time Analytics: Develop real-time analytics systems and dashboards to enable real-time insights and decision-making, leveraging technologies such as Apache Druid, Elasticsearch, or Grafana.
- Data Governance: Implement data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements in real-time data environments.
- Performance Optimization: Optimize real-time data pipelines and processing workflows for performance, scalability, and efficiency, leveraging distributed computing and streaming processing techniques.
- Monitoring and Alerting: Implement monitoring and alerting solutions to track the performance and health of real-time data infrastructure and pipelines, proactively identifying and resolving issues.
- Documentation and Best Practices: Document real-time data architecture, pipelines, and best practices, providing clear and comprehensive documentation to facilitate understanding and collaboration among team members.
- Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and business analysts, to understand requirements and deliver real-time data solutions that meet business needs.
- Mentorship and Development: Mentor junior engineers, sharing expertise and best practices in real-time data engineering, and facilitate knowledge sharing sessions within the team.
Qualifications:
- Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
- 5+ years of experience in data engineering, with a focus on real-time data technologies.
- Proficiency in real-time data streaming technologies such as Apache Kafka, Apache Flink, or Apache Spark Streaming.
- Strong programming skills in languages such as Python, Java, or Scala, with experience in distributed computing frameworks.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and services like AWS Kinesis, Azure Stream Analytics, or Google Cloud Dataflow.
- Strong understanding of event-driven architecture and stream processing concepts, with experience building event-driven systems.
- Strong problem-solving skills and analytical thinking, with the ability to design and troubleshoot complex real-time data solutions.
- Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
Benefits:
- Competitive salary: The industry standard salary for Senior Real-Time Data Engineers typically ranges from $170,000 to $230,000 per year, depending on experience and qualifications.
- Comprehensive health, dental, and vision insurance plans.
- Flexible work hours and remote work options.
- Generous vacation and paid time off.
- Professional development opportunities, including access to training programs, conferences, and workshops.
- State-of-the-art technology environment with access to cutting-edge tools and resources.
- Vibrant and inclusive company culture with opportunities for growth and advancement.
- Exciting projects with real-world impact at the forefront of data-driven innovation.
Join Us: Ready to shape the future of real-time data engineering? Apply now to join our team and be part of the data revolution!
.png)