At Best Doctors Insurance, the Cloud Data Engineer is responsible for building and maintaining cloud-database data systems that support secure, efficient management of healthcare data.
Primary Responsibilities
Cloud Data Pipeline Development:
Design and implement robust, scalable data pipelines in cloud environments (e.g., AWS, Azure, Google Cloud) to collect, process, and transform data from a variety of sources.
Cloud ETL Processes:
Develop and manage cloud-native ETL (Extract, Transform, Load) workflows using services such as Azure Data Factory, Google Cloud Dataflow, or third-party tools like Matillion.
Cloud Database Management:
Maintain and optimize cloud data warehouses (e.g., Snowflake, Amazon Redshift, Google BigQuery) and databases to ensure security, reliability, and high performance.
Data Integration:
Integrate data from APIs, on-premises systems, and third-party applications into cloud storage solutions, ensuring seamless and secure data flow across platforms.
Data Quality:
Implement data quality frameworks and enforce standards to guarantee the accuracy, consistency, and completeness of cloud-based data assets.
Collaboration:
Partner with data scientists, analysts, and business stakeholders to understand analytic requirements and deliver the necessary cloud infrastructure and data solutions.
Documentation:
Create and maintain clear documentation for cloud data systems, processes, and workflows to enable organizational learning and continuity.
Key Qualifications
Educational Background:
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Experience:
Demonstrated experience as a Data Engineer with a focus on cloud environments and large-scale data systems.
Technical Skills:
Proficiency in SQL, Python, and cloud-native programming tools.
SSIS, Snowflake, and Matillion:
Strong background with data integration and transformation tools, including expertise in SSIS and Matillion, and hands-on experience designing and optimizing data models in Snowflake or similar cloud warehouses.
Cloud Platforms:
Deep hands-on experience with at least one major cloud provider (AWS, Azure, or Google Cloud), including use of their data management and analytics services.
Security & DevOps:
Familiarity with cloud security practices, IAM, and DevOps methodologies for automating deployments and managing infrastructure as code.
Problem-Solving:
Advanced analytical and troubleshooting skills to resolve technical challenges in cloud-based data pipelines and systems.
Communication:
Strong interpersonal and communication skills, with the ability to explain cloud technologies to non-technical stakeholders.
Team Player:
Collaborative approach with experience working on distributed teams and cross-functional projects.
Preferred Qualifications
Certifications:
Relevant cloud certifications such as AWS Certified Data Analytics – Specialty, Google Cloud Professional Data Engineer, or
Microsoft Certified:
Azure Data Engineer Associate.
Advanced Analytics:
Familiarity with machine learning pipelines and advanced analytics in the cloud.
Data Visualization:
Experience connecting cloud data sources to visualization tools like Tableau, Power BI, or Looker.
Project Management:
Exposure to agile development and project management tools for delivering cloud data solutions efficiently.
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