Data Engineer (remote)

Claritev is a dynamic team dedicated to bending the cost curve in healthcare through innovative technology and data solutions. They are seeking a Data Engineer to understand business processes, implement data structures, maintain scalable data pipelines, and collaborate with various teams to fulfill data needs while ensuring compliance with regulations.

Responsibilities:

• Understand business processes and how they are modeled in various systems
• Work with business users, technology teams, and executives to understand their data needs to create innovative solutions to fulfil them
• Implement data structures, workflows, and integrations between enterprise platforms to ensure the accurate and timely execution of business processes
• Maintain scalable data pipelines to support continuing increases in data volume and complexity
• Adhere to established best practices on data integration/engineering, as well as the future of our data infrastructure
• Managing and improving the performance of our database, queries, tools, and solutions
• Creating and maintaining data warehouse, databases, tables, SQL queries, and ingestion pipelines to power report, dashboards, predictive models, and downstream analysis
• Writing complex and efficient queries to transform raw data sources into easily accessible models for our teams and reporting platforms
• Prepare data for predictive and prescriptive modeling
• Identify and analyze data patterns
• Identify ways to improve data reliability, efficiency and quality
• Work with analytics, data science, and wider engineering teams to help with automating data analysis and visualization needs, advise on transformation processes to populate data models, and explore ways to design and develop data infrastructure
• Collaborate, coordinate, and communicate across disciplines and departments
• Ensure compliance with HIPAA regulations and requirements
• Demonstrate Company's Core Competencies and values held within
• Please note due to the exposure of PHI sensitive data -- this role is considered to be a High Risk and priveleged Role
• The position responsibilities outlined above are in no way to be construed as all encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary

Requirements:

• Minimum high school diploma and four (4) years' related experience, three (3) of which should be inclusive of experience with OOP, SQL, schema designing, data modeling, designing, building, and maintaining data processing systems
• Experience with advanced analytics tools with Python and PySpark
• Experience using SQL, SPARK, and Azure Data Factory (ADF)
• Experience in triaging data issues, analyzing end-to-end data pipelines and working with business users in resolving issues
• Experience in working with data governance/data quality and data security teams and specifically data stewards and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification
• Excellent communication skills (verbal, listening and written)
• Ability to build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management
• Ability to work with both IT and business in integrating analytics and data science output into business processes and workflows
• An agile learner who brings strong problem-solving skills and enjoys working as part of a technical, cross functional team to solve complex data problems
• Able to prioritize and manage multiple projects and requests at any one time
• Strong attention to detail when identifying data relationships, trends, and anomalies
• Thinking through long-term impacts of key design decisions and handling failure scenarios
• Ability to effectively share technical information, communicate technical issues and solutions to all levels of business
• Ability to meet strict deadlines, work on multiple tasks and work well under pressure
• Bachelors' degree in computer science, information technology or a similarly relevant field is highly preferred
• Experience with Databricks and SSIS are nice to have
• Exposure to Big Data Development using Hive, Impala, Spark, and familiarity with Kafka
• Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics