Lead Cloud Data Engineer

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.

‍

Key Responsibilities:

1. Technical Leadership: Provide strategic guidance, mentorship, and technical leadership to a team of cloud data engineers, fostering a culture of excellence, innovation, and collaboration.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. Data Governance: Establish and enforce data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements in cloud data environments.
8. Performance Optimization: Lead efforts to optimize data pipelines and processing workflows for performance, scalability, and cost-effectiveness, leveraging cloud-native features and techniques.
9. 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.
10. 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.
11. 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.
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 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.
• 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 cloud data engineering? Apply now to join our team and be part of the data revolution!