Senior Data Engineer

• Senior Data Engineer
• Initial Duration: 6 months
• Location: Mountain View, CA- Only Local Candidates
• Full onsite - 5 days in a week.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes.
• Optimize data storage and retrieval systems for large-scale data sets.
• Implement and manage big data technologies, including Apache Spark and Hadoop.
• Develop and maintain data models and databases, ensuring data integrity and security.
• Collaborate with data scientists and analysts to support data-driven decision-making.
• Monitor and optimize data processing workflows for performance and efficiency.
• Ensure data quality, accuracy, and compliance with industry standards and regulations.
• Provide technical leadership and mentorship to junior team members.

Technical Skills:

• Proficient in Python for data processing and automation.
• Extensive experience with Apache Spark for distributed data processing.
• Strong knowledge of Google Cloud Platform (GCP) components, including BigQuery, Dataflow, and Pub/Sub.
• Experience with SQL and NoSQL databases.
• Familiarity with cloud-based data warehousing solutions.
• Strong understanding of data modeling, data integration, and data governance.

Professional Experience:

• 10 years of experience in data engineering roles, with a focus on big data technologies and cloud platforms.
• Proven track record of designing and implementing efficient data pipelines and ETL processes.
• Experience in leading data engineering projects and collaborating with cross-functional teams.
• Demonstrated ability to troubleshoot and resolve complex data-related issues.

Education:

Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

Additional Information:

• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.
• Ability to work in a fast-paced environment and manage multiple projects simultaneously.