Data Engineer

Data Engineer

Why This Role Matters

Data is critical to how we understand our business, support decision-making, and deliver effective solutions. In this role, you will help build and maintain the data infrastructure that transforms complex information into reliable, accessible data for reporting, analytics, predictive modeling, and downstream business needs.

As a Data Engineer, you will partner with business users, technology teams, analytics, data science, and engineering teams to understand data needs and develop scalable solutions. This is an opportunity to solve complex data challenges while helping improve the reliability, quality, performance, and accessibility of data across the organization.

What You'll Do

In this role, you will have the opportunity to:

• Design, build, and maintain scalable data pipelines, data warehouses, databases, tables, SQL queries, integrations, and data models that support reporting, dashboards, predictive modeling, and downstream analysis.

• Partner with business users, technology teams, executives, analytics, data science, and engineering teams to understand business processes and translate data needs into effective technical solutions.

• Develop and optimize complex queries and data transformations that turn raw data into reliable, accessible models for business teams and reporting platforms.

• Improve the performance, scalability, reliability, efficiency, and quality of databases, queries, tools, workflows, and data solutions as data volume and complexity grow.

• Analyze and troubleshoot data pipelines and data patterns, identify relationships, trends, anomalies, and opportunities to improve data quality and reliability.

• Support predictive and prescriptive modeling by preparing data and collaborating on automation, data analysis, visualization, and transformation processes.

• Apply established data engineering, governance, quality, security, and integration of best practices when designing and moving data solutions into production.

• Collaborate and communicate effectively across disciplines and departments while maintaining compliance with HIPAA requirements and demonstrating Claritev's Core Competencies and values.

Due to exposure to PHI and sensitive data, this position is considered a High Risk and Privileged Role. The responsibilities outlined above are not intended to be all-encompassing. Other duties, responsibilities, and qualifications may be assigned as needed.

What You Will Bring

Required Qualifications

• High school diploma or equivalent and four (4) years of related experience, including at least three (3) years of experience with object-oriented programming (OOP), SQL, schema design, data modeling, and designing, building, and maintaining data processing systems.

• Experience with advanced analytics tools using Python and PySpark.

• Experience using SQL, Spark, and Azure Data Factory (ADF).

• Experience triaging data issues, analyzing end-to-end data pipelines, and partnering with business users to resolve issues.

• Experience working with data governance, data quality, and data security teams, including data stewards and security officers, to move data pipelines into production in accordance with appropriate quality, governance, security, and certification standards.

• Ability to build and manage data pipelines supporting data transformation, data models, schemas, metadata, and workload management.

• Ability to partner with both IT and business teams to integrate analytics and data science outputs into business processes and workflows.

• Strong problem-solving skills and the ability to work effectively as part of a technical, cross-functional team to solve complex data challenges.

• Excellent verbal, written, and listening communication skills, including the ability to communicate technical issues and solutions effectively across all levels of the business.

• Ability to prioritize and manage multiple projects and requests, meet strict deadlines, and perform effectively under pressure.

• Strong attention to detail when identifying data relationships, trends, and anomalies.

• Ability to consider the long-term impact of key design decisions and effectively account for failure scenarios.

Preferred Qualifications

• Bachelor's degree in computer science, Information Technology, or a similarly relevant field.

• Experience with Databricks and SSIS.

• Exposure to Big Data development technologies, including Hive, Impala, and Spark, with familiarity with Kafka.

• Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.

Compensation

The salary range for this position is $100k - $105k.

Actual compensation is based on experience, skills, education, work location, and internal equity. This position may also be eligible for incentive compensation and the comprehensive benefits outlined in the My Total Value section.

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