Job Description
Job Description
Company Overview: Welcome to the forefront of data-driven innovation! Our company is a trailblazer in leveraging the power of data to drive transformative change and solve complex problems across industries. We're committed to building cutting-edge cloud data solutions that harness the scalability, flexibility, and power of cloud platforms. Join us and lead our efforts in shaping the future of cloud data engineering.
Position Overview: As the Lead Cloud Data Engineer, you'll spearhead our initiatives in designing, building, and optimizing cloud data solutions. You'll lead a team of skilled engineers, collaborating closely with cross-functional teams to deliver high-quality, scalable, and cost-effective data solutions. If you're a seasoned engineer with expertise in cloud data technologies and a proven track record of leadership in delivering successful data projects, we invite you to lead our team in this exciting opportunity.
Requirements
Key Responsibilities:
• Technical Leadership: Provide strategic guidance, mentorship, and technical leadership to a team of cloud data engineers, fostering a culture of excellence, innovation, and collaboration.
• Cloud Data Architecture: Lead the design and implementation of cloud data architectures on platforms such as AWS, Azure, or Google Cloud Platform (GCP), leveraging cloud-native services to build scalable, reliable, and cost-effective data solutions.
• Data Ingestion: Architect and develop robust data ingestion pipelines to collect data from diverse sources, including databases, APIs, files, and streaming sources, ensuring efficient and reliable data ingestion into cloud storage.
• Data Storage: Design and optimize data storage solutions using cloud-native storage services such as Amazon S3, Azure Data Lake Storage, or Google Cloud Storage, balancing performance, cost, and scalability requirements.
• Data Processing: Architect and implement data processing pipelines using cloud-native data processing frameworks such as Apache Spark, Apache Flink, or Google Dataflow, enabling real-time and batch data processing and analysis.
• Data Integration: Architect and implement data integration solutions to seamlessly integrate data from diverse sources and systems into cloud data solutions, ensuring interoperability and data consistency.
• Data Governance: Establish and enforce data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements in cloud data environments.
• Performance Optimization: Lead efforts to optimize data pipelines and processing workflows for performance, scalability, and cost-effectiveness, leveraging cloud-native features and techniques.
• Monitoring and Alerting: Implement robust monitoring and alerting solutions to track data pipeline performance and health, proactively identifying and resolving issues to minimize downtime and data loss.
• Documentation and Best Practices: Define and promote best practices for cloud 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, business analysts, and infrastructure teams, to understand requirements and deliver cloud 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 cloud data technologies.
• Proven leadership experience, with a track record of successfully leading cloud data engineering teams and delivering complex data projects.
• Expertise in cloud platforms such as AWS, Azure, or GCP, and proficiency in cloud-native services and tools for data storage, processing, and analytics.
• Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark or Apache Flink.
• Experience with cloud-native data processing services such as AWS Glue, Azure Data Factory, or Google Dataflow.
• Strong understanding of data integration concepts and techniques, with experience integrating data from diverse sources and systems in cloud environments.
• Strong problem-solving skills and analytical thinking, with the ability to design and troubleshoot complex cloud data solutions.
• Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
Benefits
• Competitive salary: The industry standard salary for Lead Cloud Data Engineers typically ranges from $200,000 to $300,000 per year, depending on experience and qualifications.
• Comprehe
Location: San Francisco, CA
Posted: Aug. 22, 2024, 12:41 p.m.
Apply Now Company Website