Data Engineering Manager

As a highly skilled and motivated Cloud Data Engineering Manager at Merkle, your role is critical to the development of a cutting-edge reporting platform designed to measure and optimize online marketing campaigns on Google Cloud Platform (GCP). **Key Responsibilities:** - **Data Engineering & Development:** - Design, build, and maintain scalable ETL/ELT pipelines for ingesting, processing, and transforming structured and unstructured data. - Implement enterprise-level data solutions using GCP services such as BigQuery, Dataform, Cloud Storage, Dataflow, Cloud Functions, Cloud Pub/Sub, and Cloud Composer. - Develop and optimize data architectures that support real-time and batch data processing. - Build, optimize, and maintain CI/CD pipelines using tools like Jenkins, GitLab, or Google Cloud Build. - Automate testing, integration, and deployment processes to ensure fast and reliable software delivery. - **Cloud Infrastructure Management:** - Manage and deploy GCP infrastructure components to enable seamless data workflows. - Ensure data solutions are robust, scalable, and cost-effective, leveraging GCP best practices. - **Infrastructure Automation and Management:** - Design, deploy, and maintain scalable and secure infrastructure on GCP. - Implement Infrastructure as Code (IaC) using tools like Terraform. - Manage Kubernetes clusters (GKE) for containerized workloads. - **Collaboration and Stakeholder Engagement:** - Work closely with cross-functional teams to deliver data projects aligned with business goals. - Translate business requirements into scalable, technical solutions while collaborating with team members to ensure successful implementation. - **Quality Assurance & Optimization:** - Implement best practices for data governance, security, and privacy. - Conduct thorough quality assurance to ensure the accuracy and reliability of data pipelines. - Monitor and optimize pipeline performance to meet SLAs and minimize operational costs. **Qualifications and Certifications:** - **Education:** - Bachelors or masters degree in computer science, Information Technology, Engineering, or a related field. - **Experience:** - Minimum of 7 to 9 years of experience in data engineering, with at least 4 years working on GCP cloud platforms. - Proven experience designing and implementing data workflows using GCP services. - **Certifications:** - Google Cloud Professional Data Engineer certification preferred. **Key Skills:** - **Mandatory Skills:** - Advanced proficiency in Python for data pipelines and automation. - Strong SQL skills for querying, transforming, and analyzing large datasets. - Strong hands-on experience with GCP services. - Hands-on experience with CI/CD tools such as Jenkins, GitHub or Bitbucket. - Proficiency in Docker, Kubernetes, Terraform or Ansible. - Familiarity with workflow orchestration tools like Apache Airflow or Cloud Composer. - Strong understanding of Agile/Scrum methodologies. - **Nice-to-Have Skills:** - Experience with other cloud platforms like AWS or Azure. - Knowledge of data visualization tools. - Understanding of machine learning workflows and their integration with data pipelines. **Soft Skills:** - Strong problem-solving and critical-thinking abilities. - Excellent communication skills to collaborate with technical and non-technical stakeholders. - Proactive attitude towards innovation and learning. - Ability to work independently and as part of a collaborative team.,