Unreal Gigs
Lead Real-Time Data Engineer
Unreal Gigs, New York, New York, United States,
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.RequirementsKey Responsibilities: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.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.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.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:
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.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.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 robust 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:
Define and promote best practices for real-time data engineering, ensuring clear and comprehensive documentation to facilitate understanding and collaboration among team members.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.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.BenefitsCompetitive 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!
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.RequirementsKey Responsibilities: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.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.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.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:
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.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.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 robust 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:
Define and promote best practices for real-time data engineering, ensuring clear and comprehensive documentation to facilitate understanding and collaboration among team members.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.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.BenefitsCompetitive 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!