Senior Engineer, Data Engineering

Claritev helps make healthcare more transparent and affordable through data, technology, and expertise. The Senior Data Engineer develops and deploys enterprise data engineering and integration solutions, collaborating with data architects, machine learning, analytics, and engineering teams to build scalable pipelines, integrations, data models, and infrastructure while supporting data quality, security, governance, and HIPAA compliance.

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
• Design, organize, and implement data structures, workflows, and integrations between enterprise platforms to ensure the accurate and timely execution of business processes
• Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity
• Guiding decisions and establishing 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 reports(Tableau), 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
• Document high- and low-level technical design
• Draw performance reports and strategic proposals from analyses results for senior data science leadership
• 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 privileged 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 five years of relevant experience within data engineering
• Required licensures, professional certifications, and/or Board certifications as applicable
• Minimum of 3 years of experience with OOP, SQL, schema designing, data modeling, designing, building, and maintaining data processing systems
• Strong experience with advanced analytics tools for Object-Oriented/object function scripting using languages such as R, Python, Java, others
• Database development experience using SQL, SPARK, or BigQuery and experience with a variety of relational, NoSQL oriented databases like Hadoop, MongoDB, Cassandra
• Extensive 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
• Experience building infrastructure required for optimal extraction, transformation, and loading of data from diverse data resources
• Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines
• Exposure to containerization using Docker, Kubernetes etc
• Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
• Excellent communication skills (verbal, listening and written)
• Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management
• 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 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
• A thought leader when approaching technical challenges
• Ability to provide mentoring to a team of data engineers
• Ability to prioritize and manage multiple projects and requests at any one time
• 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
• Individual in this position must be able to work in a standard office environment which requires sitting and viewing monitor(s) for extended periods of time, operating standard office equipment such as, but not limited to, a keyboard, copier and telephone
• Python
• PySpark
• SQL / T-SQL
• Data pipeline development and optimization
• Cloud-based data engineering experience (Azure, AWS, or GCP)
• Experience supporting AI/ML data initiatives-Claude Code, OpenAI Codex, AI Agent
• Bachelors' degree in computer science, information technology or a similarly relevant field is highly preferable
• Big Data Development experience using Hive, Impala, Spark, and familiarity with Kafka (preferred)