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What's this role about?

* *Lead and Oversee Data Architecture:* Design, implement, and manage scalable, high-performance data architectures on AWS and Databricks platforms to support business needs. * *End-to-End Development Lifecycle:* Participate in all phases of the application development lifecycle, from requirements gathering to deployment and maintenance. * *Technical Leadership:* Provide technical guidance and mentorship to data engineers, ensuring best practices in coding, architecture, and overall data management. * *Solution Design:* Collaborate with stakeholders to understand business requirements and translate them into effective, scalable data solutions. Participate in both logical and physical design phases. * *Complex Problem Solving:* Address complex technical challenges and provide innovative solutions, ensuring robustness, scalability, and performance. * *Quality Assurance:* Review code and enforce quality standards within the team, fostering a culture of continuous improvement. * *Agile Collaboration:* Work as an integral part of a Scrum team, contributing to sprint planning, execution, and retrospectives. * *Cross-functional Collaboration:* Engage in a broad range of complex technical or professional work activities, collaborating with cross-functional teams to ensure seamless data integration and management. * *Strategic Direction:* Work under general direction within a clear framework of accountability, providing substantial personal responsibility and autonomy in strategic decisions.

What skills and experience do you need?

* *Extensive Data Engineering Experience:* Proven experience as a Data Engineer in Databricks environments, with a deep understanding of Databricks data engineering tools (Unity Catalog, Delta Lake, Spark SQL, Spark Streaming, Delta Sharing). * *AWS Expertise:* Extensive experience in configuring and optimizing AWS data services (S3, Lambda, Glue, Step Functions, DynamoDB, Kinesis, Athena, EventBridge, SNS) for seamless data integration and event-driven workflows. * *Advanced Data Pipeline Management:* Expertise in developing and maintaining data pipelines using Python within an AWS-based platform, ensuring efficient data processing and management. * *Data Automation and Ingestion:* Strong skills in data automation and ingestion, utilizing tools and frameworks to streamline data workflows. * *Infrastructure as Code (IaC):* Proficiency in implementing IaC using AWS CDK to manage and automate cloud resources effectively. * *Apache Iceberg:* Experience utilizing Apache Iceberg to enhance data storage and organization for improved scalability and performance. * *Version Control and CI/CD:* Manage version control and CI/CD workflows using GitHub, leveraging GitHub Actions for continuous integration and deployment. * *Monitoring and Observability:* Enhance monitoring and observability of data pipelines using Datadog, optimizing performance and reliability. * *Client-facing and Communication Skills:* Excellent client-facing skills with the ability to communicate complex technical concepts to non-technical stakeholders. * *English Proficiency:* Strong English language skills, both written and verbal. * *Agile Methodologies:* Experience working within an Agile delivery framework, contributing to continuous improvement and efficient project delivery.

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