Senior Data Engineer

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🕒 April 27

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Enable Data

WebsiteLinkedInAll Job Openings

51 - 200 employees

☁️ SaaS

⚕️ Healthcare Insurance

🏢 Enterprise

SaaS • Healthcare Insurance • Enterprise

Enable Data is a company that offers modern IT solutions to empower its customers by leveraging innovative data analytics and cloud platforms to drive increased value across their business ecosystem. They specialize in the implementation of large-scale SAS applications, distributed rules engines for processing health-related data, and managing data ingest frameworks. Enable Data serves industries requiring advanced data analytics and IT solutions, with a particular focus on healthcare quality and big data management.

📋 Description

• Design, develop, and maintain scalable and robust data solutions in the cloud using Apache Spark and Databricks. • Gather and analyze data requirements from business stakeholders and identify opportunities for data-driven insights. • Build and optimize data pipelines for data ingestion, processing, and integration using Spark and Databricks. • Ensure data quality, integrity, and security throughout all stages of the data lifecycle. • Collaborate with cross-functional teams to design and implement data models, schemas, and storage solutions. • Optimize data processing and analytics performance by tuning Spark jobs and leveraging Databricks features. • Provide technical guidance and expertise to junior data engineers and developers. • Stay up-to-date with emerging trends and technologies in cloud computing, big data, and data engineering. • Contribute to the continuous improvement of data engineering processes, tools, and best practices.

🎯 Requirements

• Bachelor's or Master's degree in computer science, engineering, or a related field. • 10+ years of experience as a Data Engineer, Software Engineer, or similar role, with a focus on building cloud-based data solutions. • Strong experience with cloud platforms such as Azure • Proficiency in Apache Spark and Databricks for large-scale data processing and analytics. • Experience in designing and implementing data processing pipelines using Spark and Databricks. • Strong knowledge of SQL and experience with relational and NoSQL databases. • Experience with data integration and ETL processes using tools like Apache Airflow or cloud-native orchestration services. • Good understanding of data modeling and schema design principles. • Experience with data governance and compliance frameworks. • Excellent problem-solving and troubleshooting skills. • Strong communication and collaboration skills to work effectively in a cross-functional team. • Relevant certifications in cloud platforms, Spark, or Databricks are a plus.