Data Architect Senior

**Responsibilities**:- Leading the architecture and implementation of Spark and Databricks-based ETL frameworks for large-scale enterprise systems.- Designing and developing high-throughput data pipelines using Spark core and streaming technologies.- Implementing and enforcing architectural standards and frameworks to ensure a flexible and scalable data environment.- Collaborating with cross-functional teams to gather requirements, analyze data, and design effective solutions.- Utilizing tools such as Apache Airflow, Azure Data Factory, and Change Data Capture (CDC) for orchestrating and managing data workflows.- Playing a key role in DevOps activities, including deployment of Spark jobs and infrastructure setup.- Providing mentorship and technical guidance to junior team members.- Staying updated with the latest industry trends and technologies in data engineering and analytics.**Qualifications**:- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.- 5+ years of hands-on IT experience, with a strong focus on ETL and Python technologies.- Proven expertise in designing and implementing data solutions using Spark and Databricks.- Extensive experience with Spark core and streaming development.- Solid understanding of Python programming for data manipulation and transformation.- Hands-on experience with Databricks Workflows, Delta Live Tables, and Unity Catalog.- Proven ability to troubleshoot and optimize SPARK queries for analytics and business intelligence use cases.- Proficiency in utilizing Apache Airflow, Azure Data Factory, and Change Data Capture (CDC) for data orchestration.- Basic knowledge of DevOps practices for managing Spark job deployments.- Databricks Certified Certification in Advanced Data Engineering is a plus.- Strong problem-solving skills and the ability to work effectively in a collaborative team environment.- Excellent communication and interpersonal skills.**We are an equal opportunity employer