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Lead Data Systems Engineer
1 month ago
Position Overview: As the Lead Data Systems Engineer, you will play a pivotal role in leading our data systems engineering initiatives and driving the design, implementation, and optimization of our data systems infrastructure. You will lead a team of skilled engineers, collaborating closely with cross-functional teams to deliver high-quality, scalable, and reliable data systems solutions that meet the evolving needs of our data-driven organization. If you're a seasoned engineer with expertise in data systems 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 data systems engineers, fostering a culture of excellence, innovation, and collaboration.
- Data Systems Architecture: Lead the design and implementation of scalable and reliable data systems architecture to support the organization's data needs, including data storage, processing, and analytics.
- Data Storage Solutions: Architect and implement data storage solutions, including relational databases, NoSQL databases, data warehouses, and data lakes, ensuring optimal performance, reliability, and scalability.
- Data Processing Frameworks: Lead the implementation and optimization of data processing frameworks and technologies, such as Apache Hadoop, Apache Spark, and Apache Flink, to enable efficient data processing and analysis.
- Data Pipeline Development: Lead the development and maintenance of data pipeline solutions to ingest, transform, and deliver data from various sources to target systems, ensuring seamless data flow and interoperability.
- Data Integration: Lead efforts to integrate data from diverse sources and systems into data systems infrastructure, ensuring data consistency, integrity, and security.
- Data Governance: Establish and enforce data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements.
- Performance Optimization: Lead efforts to optimize data systems performance through indexing, partitioning, and other techniques, ensuring scalability and responsiveness for analytical and reporting needs.
- Monitoring and Alerting: Implement robust monitoring and alerting systems to track data systems performance and health, proactively identifying and resolving issues to minimize downtime and data loss.
- Documentation and Best Practices: Define and promote best practices for data systems engineering, ensuring clear and comprehensive documentation to facilitate understanding and collaboration among team members.
- Collaboration: Collaborate closely with cross-functional teams, including data engineers, data scientists, and business analysts, to understand requirements and deliver data systems 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 or systems engineering, with a focus on data systems technologies.
- Proven leadership experience, with a track record of successfully leading data systems engineering teams and delivering complex projects.
- Expertise in data storage technologies such as relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), data warehouses (e.g., Snowflake, Redshift), and data lakes (e.g., Amazon S3, Azure Data Lake Storage).
- 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 platforms such as AWS, Azure, or Google Cloud Platform, and services like 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 data systems infrastructure.
- Strong problem-solving skills and analytical thinking, with the ability to design and troubleshoot complex data systems issues.
- 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 Data Systems 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 data systems engineering? Apply now to join our team and be part of the data revolution
