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 cutting-edge data systems that enable efficient data management, processing, and analysis. Join us and be part of a dynamic team shaping the future of data systems engineering.

Position Overview: As a Senior Data Systems Engineer, you'll play a critical role in designing, building, and optimizing our data systems infrastructure. You'll work on challenging projects, from architecting data storage solutions to implementing data processing frameworks, to support the needs of our data-driven organization. If you're a seasoned engineer with expertise in data systems technologies and a passion for building scalable and reliable data systems, we want you on our team.

Key Responsibilities:

  1. Data Systems Architecture: Design and implement scalable and reliable data systems architecture to support the organization's data needs, including data storage, processing, and analytics.
  2. 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.
  3. Data Processing Frameworks: Implement and optimize data processing frameworks and technologies, such as Apache Hadoop, Apache Spark, and Apache Flink, to enable efficient data processing and analysis.
  4. Data Pipeline Development: Develop and maintain data pipeline solutions to ingest, transform, and deliver data from various sources to target systems, ensuring seamless data flow and interoperability.
  5. Data Integration: Integrate data from diverse sources and systems into data systems infrastructure, ensuring data consistency, integrity, and security.
  6. Data Governance: Establish and enforce data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements.
  7. Performance Optimization: Optimize data systems performance through indexing, partitioning, and other techniques, ensuring scalability and responsiveness for analytical and reporting needs.
  8. Monitoring and Alerting: Implement monitoring and alerting systems to track data systems performance and health, proactively identifying and resolving issues to minimize downtime and data loss.
  9. Documentation and Best Practices: Document data systems designs, processes, and best practices, providing clear and comprehensive documentation to facilitate understanding and collaboration among team members.
  10. Collaboration: Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to understand requirements and deliver data systems solutions that meet business needs.
  11. Mentorship and Development: Mentor and coach junior engineers, providing guidance, support, and opportunities for skill development and career growth.

Qualifications:

  • Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
  • 5+ years of experience in data engineering or systems engineering, with a focus on data systems technologies.
  • Proficiency 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.
  • 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 work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.

Benefits:

  • Competitive salary: The industry standard salary for Senior Data Systems Engineers typically ranges from $170,000 to $230,000 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 shape the future of data systems engineering? Apply now to join our team and be part of the data revolution!

Full Time

8 to 5

Remote

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