Site Reliability Engineer

Skills

Design build and maintain the infrastructure and data pipelines to support data transformation data structures metadata dependency and workload management. Develop and maintain scalable reliable and cost-effective data solutions using AWS technologies and big data tools like Databricks Airflow and Dremio. Implement robust monitoring and alerting systems using tools such as Datadog to ensure proactive management of the production environments. Work closely with data scientists and analytics teams to engineer and optimize data models using DBT (Data Build Tool) and ensure seamless data flow across all segments. Enhance data validation and data quality metrics integration within data pipelines to ensure accuracy and reliability of data. Automate manual processes optimize data delivery and re-design infrastructure for greater scalability. Handle the deployment of additional AWS services such as Lambda functions and manage data storage solutions. Collaborate with IT and DevOps teams to enhance system performance and reliability through AWS solutions such as SNS SQS and Elastic Load Balancer. Engage in continuous improvement efforts to enhance performance and provide increased functionality across data platforms. Provide support and mentorship to offshore teams ensuring best practices in coding testing and deployment are followed. Troubleshoot complex issues across multiple databases and work with various stakeholders to ensure robust architecture and operational standards are maintained.

Description

We are currently seeking a highly skilled Data Reliability Engineer to join our team. This role requires a blend of expertise in data pipeline technologies and Site Reliability Engineering (SRE) principles to ensure the highest standards of data reliability and system performance.

Responsibilities

• Strong proficiency in Apache Airflow, Python programming, and AWS cloud services.
• Experience with real-time monitoring tools such as Datadog.
• Expertise in data transformation tools like DBT and Dremio.
• Strong experience with Databricks and AWS Lambda.
• Excellent verbal and written communication skills, capable of working with cross-functional teams and managing relationships with business stakeholders.
• Nice to Have Skills:
• Familiarity with AWS services such as SNS, SQS, Elastic Load Balancer, CodeBuild, Code Pipeline, ECR, and EKS.
• Experience with both Linux and Windows operating systems.
• Knowledge of Microsoft Azure Data Lake, Synapse, and additional Python scripting.

Educational Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
• Proven experience as a Data Engineer, Data Reliability Engineer, or in a similar role in an SRE environment.
• Demonstrable experience with end-to-end monitoring of data pipelines and implementing reliability in data systems.