Remote Senior Data Systems Engineer

Description:

• Design and implement scalable and reliable data systems architecture to support data storage, processing, and analytics needs.
• Architect and implement various data storage solutions like relational databases, NoSQL databases, data warehouses, and data lakes for optimal performance and scalability.
• Implement and optimize data processing frameworks such as Apache Hadoop, Apache Spark, and Apache Flink for efficient data processing and analysis.
• Develop and maintain data pipeline solutions to ingest, transform, and deliver data from diverse sources to target systems.
• Integrate data from different sources into data systems infrastructure while ensuring data consistency, integrity, and security.
• Establish and enforce data governance policies to maintain data quality, security, and compliance with regulations.
• Optimize data systems performance through indexing, partitioning, and other techniques for scalability and responsiveness.
• Implement monitoring and alerting systems to track data systems performance and health, resolving issues proactively.
• Document data systems designs, processes, and best practices for team collaboration and understanding.
• Collaborate with cross-functional teams to deliver data systems solutions meeting business requirements.
• Mentor and coach junior engineers for skill development and career growth.

Requirements:

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
• 5+ years of experience in data engineering or systems engineering focusing on data systems technologies.
• Proficiency in 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 Python, Java, or Scala, with experience in Apache Spark or Apache Flink.
• Experience with cloud platforms like AWS, Azure, or Google Cloud Platform, and services like AWS Glue, Azure Data Factory, or Google Dataflow.
• Understanding of data integration concepts and techniques, with experience in integrating data from diverse sources.
• Strong problem-solving and analytical skills for designing and troubleshooting complex data systems issues.
• Excellent communication and collaboration skills for working in cross-functional teams and explaining technical concepts to non-technical stakeholders.

Benefits:

• Competitive salary ranging from $170,000 to $230,000 per year based 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 training programs, conferences, and workshops.
• State-of-the-art technology environment with access to cutting-edge tools.
• Vibrant and inclusive company culture with growth and advancement opportunities.
• Exciting projects with real-world impact in the data-driven innovation field.