Cloud Data Platform Leader

Our people work in a variety of projects to solve clients' toughest data problems by combining industry experience, consulting, and analytical skills to create a lasting impact. Our projects and clients vary greatly, and your responsibilities will differ based on your level of experience/skillset and the focus of the client engagement, your role is likely to include some or all the following:

• Placing a focus upon exceeding client expectations and delivering against our continuous improvement goals, taking a client problem, and turning it into a technical solution
• Data Ingestion: Design, implement, and manage data ingestion pipelines to collect and ingest data from various sources into the cloud data platform. This might involve using tools like Apache Kafka, AWS Kinesis, or Azure Event Hubs.
• Data Transformation: Develop and maintain data transformation processes to clean, enrich, and structure data for analytics and reporting purposes. This often involves using ETL (Extract, Transform, Load) tools or scripting languages like Python.
• Data Integration: Integrate different data sources and systems to ensure data consistency and accessibility. This may involve setting up data connectors or APIs.
• Data Security: Implement and enforce data security measures, including encryption, access controls, and compliance with data privacy regulations such as GDPR or HIPAA.
• Performance Tuning: Monitor and optimize the performance of the cloud data platform to ensure efficient data processing and query performance. This may involve adjusting configurations, indexing, and caching.
• Automation and Orchestration: Create and maintain automation scripts and workflows to manage data pipelines, backups, and routine tasks. Infrastructure as Code (IAC) tools like Terraform or AWS CloudFormation may be used.
• Monitoring and Alerting: Set up monitoring and alerting systems to proactively identify and address issues with data pipelines, platform health, and data quality. Tools like Prometheus, Grafana, or cloud-native monitoring solutions can be employed.
• Documentation and Collaboration: Document data platform architecture, processes, and best practices. Collaborate with data engineers, data scientists, and other stakeholders to understand their requirements and ensure the data platform meets their needs.