Data Engineer (remote)

Role Overview

As a Data Engineer at Claritev, you will design, build, and maintain data structures, pipelines, and integrations that enable business processes and analytics use cases in healthcare.

Responsibilities

• Understand business processes and how they are modeled across enterprise systems.
• Partner with business users, technology teams, and executives to define data needs and build solutions.
• Implement data structures, workflows, and integrations between enterprise platforms for accurate and timely execution.
• Build and maintain scalable data pipelines as data volume and complexity grow.
• Follow best practices for data integration and data infrastructure.
• Manage and improve performance of databases, queries, tools, and solutions.
• Create and maintain data warehouses, databases, tables, SQL queries, and ingestion pipelines for:
  • reporting and dashboards
  • predictive models
  • downstream analysis
• Write complex, efficient SQL to transform raw sources into accessible data models.
• Prepare data for predictive and prescriptive modeling; analyze data patterns.
• Improve data reliability, efficiency, and quality.
• Collaborate with analytics, data science, and engineering teams to automate data analysis/visualization and advise on transformation processes.
• Communicate and coordinate across disciplines and departments.
• Ensure HIPAA compliance (role involves exposure to PHI; treated as high-risk/privileged).

Requirements

• Minimum high school diploma plus 4 years related experience.
• 3+ years including experience with:
  • OOP
  • SQL
  • schema design and data modeling
  • designing/building/maintaining data processing systems
• Experience with Python and PySpark and advanced analytics tools.
• Experience using SQL, Spark, and Azure Data Factory (ADF).
• Ability to triage data issues and analyze end-to-end data pipelines with business users.
• Experience with data governance/data quality and data security; work with data stewards/security officers to move pipelines into production with appropriate standards and certifications.
• Strong communication skills (verbal, listening, written).
• Ability to build/manage pipelines covering transformations, models, schemas, metadata, and workload management.
• Ability to work effectively with both IT and business stakeholders.

Nice to Have

• Experience with Databricks and SSIS.
• Big data development using Hive, Impala, Spark, and familiarity with Kafka.
• Exposure to machine learning/data science (including computer vision, AI), statistics, or applied mathematics.