Lead Real-Time Data Engineer

Company Overview: Welcome to the forefront of data-driven innovation! Our company is at the cutting edge of leveraging 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 lead our efforts in shaping the future of real-time data engineering.

Position Overview: As the Lead Real-Time Data Engineer, you'll lead our initiatives in designing, building, and optimizing real-time data infrastructure. You'll spearhead the development of scalable, reliable, and efficient systems for ingesting, processing, and analyzing real-time data streams. If you're a seasoned engineer with expertise in real-time data technologies and a proven track record of leadership in delivering successful projects, we invite you to lead our team in this exciting opportunity.

Requirements

Key Responsibilities:

1. Technical Leadership: Provide strategic guidance, mentorship, and technical leadership to a team of real-time data engineers, fostering a culture of excellence, innovation, and collaboration.
2. Real-Time Data Architecture: Lead the design and implementation of scalable and reliable architecture for real-time data processing and analytics, encompassing data ingestion, processing, and serving layers.
3. Streaming Data Pipelines: Architect and develop robust real-time data streaming pipelines using technologies such as Apache Kafka, Apache Flink, or Apache Spark Streaming, ensuring low-latency and high-throughput processing.
4. 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.
5. Data Integration: Lead efforts to integrate real-time data streams from diverse sources and systems into the real-time data infrastructure, ensuring data consistency, integrity, and quality.
6. Real-Time Analytics: Develop real-time analytics systems and dashboards to enable timely insights and decision-making, leveraging technologies such as Apache Druid, Elasticsearch, or Grafana.
7. Data Governance: Implement data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements in real-time data environments.
8. Performance Optimization: Optimize real-time data pipelines and processing workflows for performance, scalability, and efficiency, leveraging distributed computing and streaming processing techniques.
9. Monitoring and Alerting: Implement robust monitoring and alerting solutions to track the performance and health of real-time data infrastructure and pipelines, proactively identifying and resolving issues.
10. Documentation and Best Practices: Define and promote best practices for real-time data engineering, ensuring clear and comprehensive documentation to facilitate understanding and collaboration among team members.
11. Collaboration: Collaborate closely 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.
12. Mentorship and Development: Mentor and coach junior engineers, providing guidance, support, and opportunities for skill development and career growth, and foster a culture of continuous learning and improvement within the team.

Qualifications:

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
• 8+ years of experience in data engineering, with a focus on real-time data technologies.
• Proven leadership experience, with a track record of successfully leading real-time data engineering teams and delivering complex projects.
• Expertise 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 Lead Real-Time Data Engineers typically ranges from $200,000 to $300,000 per year, depending on experience and qualifications.
• Comprehensive benefits package, including health insurance, retirement plans, and wellness programs.
• Flexible work arrangements, including remote work options and flexible hours.
• 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 lead the charge in real-time data engineering? Apply now to join our team and be part of the data revolution!