Sr. Site Reliability Engineer (need Locals to TX)

• 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.

• 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.

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