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Data Reliability Engineer
2 months ago
Raso360 is seeking a highly skilled Sr. 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.
Key Responsibilities:- Design and Maintain Infrastructure: Design, construct, and maintain infrastructure and data pipelines to manage data transformation, data structures, metadata, dependencies, and workload processes.
- Develop Scalable Data Solutions: Develop scalable, efficient, and cost-effective data solutions leveraging AWS technologies and big data tools like Databricks, Airflow, and Dremio.
- Implement Monitoring Systems: Implement advanced monitoring and alerting systems using tools like Datadog to proactively manage and monitor production environments.
- Collaborate with Data Scientists: Collaborate with data scientists and analytics teams to design and optimize data models using DBT (Data Build Tool), ensuring smooth data flow across various systems.
- Improve Data Pipelines: Improve data pipelines with integrated data validation and quality metrics to ensure accuracy and dependability of data.
- Automate Processes: Automate manual processes, optimize data delivery, and redesign infrastructure to support higher scalability.
- Deploy AWS Services: Deploy additional AWS services such as Lambda functions and oversee the management of data storage solutions.
- Enhance System Performance: Work closely with IT and DevOps teams to enhance system performance and reliability using AWS tools like SNS, SQS, and Elastic Load Balancer.
- Provide Guidance: Provide guidance and mentorship to offshore teams, ensuring best practices are upheld in coding, testing, and deployment.
- Resolve Complex Issues: Resolve complex issues across multiple databases and collaborate with stakeholders to maintain a robust architecture and high operational standards.
- Education: Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
- Experience: Proven experience as a Data Engineer, Data Reliability Engineer, or in a similar role in an SRE environment.
- Skills: Strong proficiency in Apache Airflow, Python programming, and AWS cloud services.
- Tools: Experience with real-time monitoring tools such as Datadog, data transformation tools like DBT and Dremio, and big data tools like Databricks.
- Communication: Excellent verbal and written communication skills, capable of working with cross-functional teams and managing relationships with business stakeholders.
- AWS Services: Familiarity with AWS services such as SNS, SQS, Elastic Load Balancer, CodeBuild, CodePipeline, ECR, and EKS.
- Operating Systems: Experience with both Linux and Windows operating systems.
- Additional Tools: Knowledge of Microsoft Azure Data Lake, Synapse, and additional Python scripting.
