Master Data Architect Leader
1 week ago
We are seeking an exceptional Senior Data Architect to join our Data and Analytics organization. In this critical role, you will play a key part in designing, implementing, and overseeing a robust and scalable data architecture.
About the Role
You will be responsible for developing comprehensive data architecture solutions, including data models, metadata, and data integration frameworks. This will involve ensuring scalability and reliability while collaborating with data engineers and data scientists to integrate data from various sources into a cohesive data architecture.
The ideal candidate will have a deep understanding of data management, modeling, and integration, as well as expertise in data platforms and services like Databricks, Dataiku, and AWS native data offerings. You will also have solid experience with big data technologies (Databricks, Apache Spark, Hadoop, Kafka) and cloud services (AWS, Azure) related to data processing and storage.
What We Offer
We offer a competitive salary range of $180,000 - $220,000 per year, based on experience, plus a comprehensive benefits package that includes medical, dental, and vision insurance, wellness programs, retirement plans, and generous paid leave. Additionally, you will have opportunities for career growth, leadership development, and professional networking within our organization.
Requirements
- Bachelor's or master's degree in Computer Science, MIS, or related field, or equivalent combination of education and experience.
- 10+ years of experience in data architecture, data modeling, and database design, with a proven track record in designing and operating large-scale data systems.
- Expertise in data integration and ETL/ELT workflows, with hands-on experience in tools such as Apache Airflow and Talend.
- Fluent in Infrastructure-as-Code paradigms (e.g., Terraform).
- Comprehensive knowledge of data platforms and services like Databricks, Dataiku, and AWS native data offerings.
- Solid experience with big data technologies (Databricks, Apache Spark, Hadoop, Kafka) and cloud services (AWS, Azure) related to data processing and storage.
- Proficient in SQL and programming languages relevant to data architecture (Python, Java, Scala).
- Familiarity with machine learning model deployment and management practices is a plus.
- Fluent with CI/CD workflows and automation.
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