Senior Data Ops Engineer

Key Skills

Agile methodologies, Ansible, AWS, Azure, Bash scripting, Databricks, DevOps, ETL frameworks, Google BigQuery, Grafana, MySQL, Postgres, PostgreSQL, Puppet, Python Programming, SQL

Job Description

Data Ops team will own the company's data infrastructure, ensuring our data infrastructure's availability, scalability, security, and reliability while providing exceptional support to the customers, including operators, developers, analysts, and research scientists. This team will provide first and second levels of support to internal customers on requests related to data pipelines and access management. The ideal candidate would be passionate about data management and want to contribute to a dynamic company’s growth and success. The successful candidate will have strong technical skills and the ability to mentor and support junior team members to achieve project goals.

Role Responsibilities:

• Run the data infrastructure in the production environment by monitoring availability and taking a holistic view of system health
• Provide operational first & second-line support for multiple large-scale data Products, Services, and ML models
• Participate in on-call rotations to ensure 24/7 availability of data infrastructure and services. Triage and debug production issues
• Measure and optimize system performance with an eye toward pushing our capabilities forward, getting ahead of customer needs, and innovating for continual improvement
• Partner with development teams to improve services through rigorous testing and release procedures
• Continuously improve our data infrastructure and processes to ensure optimal performance, reliability, and security
• Provide technical guidance and support to team members and stakeholders
• Mentor and support junior team members to achieve project goals

Skills Needed:

• BS or MS degree in Computer Science, Engineering, or a related technical field
• 5+ years of experience in a DataOps, Data Management, Data Engineering, or similar role working with event instrumentation, data pipelines, and data warehouses
• Strong experience in data integration, ETL, data modeling, and data pipeline tools such as Apache Kafka, Apache Airflow, dbt, and AWS Glue
• Strong SQL skills
• Experience with modern data warehouses, like Snowflake or BigQuery, and Databricks Lakehouse Platform
• Strong skills in SQL and database technologies such as MySQL, PostgreSQL, and MongoDB
• Experience with cloud computing, such as AWS or Azure
• Strong scripting skills (Python, Bash, etc.) and experience with automation tools (Ansible, Chef, Puppet, etc.)
• Experience with monitoring and logging tools such as Prometheus, Grafana, and ELK stack
• Experience with DevOps and Agile methodologies
• Expertise in breaking down complex problems, documenting solutions, and sequencing work to make iterative improvements
• Excellent communication and interpersonal skills

Remote roles in India are available in all territories.