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We are looking for a Senior Data Engineer to develop and optimize enterprise data systems that support analytics and digital solutions. In this role, you will design and implement robust data architectures, ensuring seamless data integration and transformation processes across the organization. Your expertise will drive the creation of reliable pipelines and scalable infrastructure, enabling advanced analytics and machine learning capabilities.
Job Responsibility:
Design and implement scalable data pipelines using Databricks, Spark, and Delta Lake to support enterprise-level analytics
Develop and maintain efficient data models tailored for AI, analytics, and operational systems
Lead Master Data Management initiatives to establish unified and accurate data records across platforms
Create batch and near-real-time data processing workflows for structured and semi-structured datasets
Collaborate with AI and software development teams to ensure delivery of high-quality datasets for machine learning
Define and enforce data architecture standards, ensuring scalability, reliability, and governance
Troubleshoot and optimize data systems to maintain performance and reliability in complex environments
Partner with cloud and IT teams to integrate modern data platforms and ensure seamless functionality
Requirements:
Minimum of 8 years of experience in data engineering or related roles
Proficiency with Databricks, Apache Spark, Delta Lake, and Python
Strong background in building enterprise-scale ETL pipelines and managing complex data environments
Familiarity with cloud data platforms such as AWS, Azure, and Google Cloud
Experience with Master Data Management and creating unified data records
Solid understanding of SQL and distributed systems
Ability to develop scalable and reliable data architectures
Excellent problem-solving skills and a passion for data-driven solutions
What we offer:
medical, vision, dental, and life and disability insurance