More than 3 months ago
Job Description
Company Overview: Welcome to the forefront of data-driven innovation! Our company is dedicated to harnessing the power of data to drive transformative change and solve complex problems across industries. We're committed to building scalable and reliable data infrastructure that enables advanced analytics, machine learning, and business intelligence. Join us and lead our team in shaping the future of data engineering.
Position Overview: As the Lead Data Engineer, you'll be responsible for leading our data engineering efforts and driving the design, development, and maintenance of our data infrastructure and pipelines. You'll lead a team of talented data engineers and collaborate closely with cross-functional teams to deliver end-to-end data solutions that support the needs of our data-driven organization. If you're a seasoned data engineer with expertise in data engineering technologies and a track record of leading successful data projects, we want you on our team.
Requirements
Key Responsibilities:
Qualifications:
Benefits
Join Us: Ready to lead the charge in data engineering? Apply now to join our team and shape the future of data-driven innovation!
Position Overview: As the Lead Data Engineer, you'll be responsible for leading our data engineering efforts and driving the design, development, and maintenance of our data infrastructure and pipelines. You'll lead a team of talented data engineers and collaborate closely with cross-functional teams to deliver end-to-end data solutions that support the needs of our data-driven organization. If you're a seasoned data engineer with expertise in data engineering technologies and a track record of leading successful data projects, we want you on our team.
Requirements
Key Responsibilities:
- Technical Leadership: Lead a team of data engineers, providing guidance, mentorship, and technical leadership in data engineering best practices and technologies.
- Data Infrastructure Design: Lead the design and architecture of our data infrastructure, including data warehouses, data lakes, and data pipelines, ensuring scalability, reliability, and performance.
- Data Pipeline Development: Lead the development of scalable and efficient data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data from diverse sources.
- Data Modeling: Lead the design and implementation of data models and schemas to support analytical and operational requirements, ensuring data integrity, consistency, and performance.
- Data Governance: Establish and enforce data governance policies and best practices to ensure data quality, security, and compliance with regulatory requirements.
- Performance Optimization: Lead efforts to optimize data pipelines and queries for performance and efficiency, identifying and addressing bottlenecks and inefficiencies to improve system scalability and reliability.
- Monitoring and Alerting: Lead the implementation of monitoring and alerting systems to track data pipeline performance and health, detecting and mitigating issues proactively to minimize downtime and data loss.
- Documentation and Best Practices: Define and promote best practices for data engineering, documentation, and usage, ensuring 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 stakeholders, to understand requirements and deliver data solutions that meet business needs.
- Mentorship and Development: Mentor junior engineers, providing guidance, support, and opportunities for growth and development in their data engineering careers.
Qualifications:
- Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
- 7+ years of experience in data engineering, with a focus on designing, building, and maintaining data infrastructure and pipelines.
- Leadership experience, with a demonstrated ability to lead and mentor a team of engineers.
- Proficiency in programming languages such as Python, Java, or Scala, and experience with data engineering frameworks and tools such as Apache Spark, Apache Kafka, Apache Airflow, or similar.
- Strong understanding of data modeling concepts and techniques, with experience designing and implementing data models and schemas for relational and non-relational databases.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and familiarity with cloud-based data services such as Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.
- Experience with SQL and NoSQL databases, data warehousing, and ETL/ELT processes.
- Strong problem-solving skills and analytical thinking, with the ability to troubleshoot complex data issues and optimize system performance.
- 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 Data Engineers typically ranges from $200,000 to $300,000 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 lead the charge in data engineering? Apply now to join our team and shape the future of data-driven innovation!
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