Archived listing. The details below describe a past opening.
Required Skills & Experience
- 5-7+ years of experience in Data Engineering, Analytics Engineering, or a related field.
- Advanced SQL development and data analysis experience.
- Strong Python programming skills for data transformation, business logic development, and automation.
- Experience with Google BigQuery.
- Experience working within Google Cloud Platform (GCP).
- Experience developing and maintaining Airflow Composer workflows.
- Experience working with APIs and Kafka-based data integrations.
- Knowledge of Google Cloud Storage (GCS).
- Experience working within GitHub and version-controlled development environments.
- Strong understanding of data validation, data reconciliation, and troubleshooting techniques.
- Ability to navigate and work within SQL Server environments, including reviewing and validating legacy code.
- Exceptional communication and documentation skills with the ability to explain technical concepts to business users. Strong analytical and problem-solving abilities.
Nice to Have Skills & Experience
- Experience with Databricks (not required but a plus).
- Experience supporting large-scale cloud modernization or migration initiatives.
- Familiarity with enterprise data platform architectures.
- Experience working with AI-assisted development tools.
- Healthcare industry experience is not required.
Job Description
Overview
We are seeking a Data Engineer to join a Specialty Care Partnerships team that provides data services and analytics support to external healthcare partners. This team recently completed a major modernization initiative, migrating from a legacy on-premises SQL environment to a cloud-based GCP platform. The ideal candidate is a strong analytical problem solver who can work closely with business stakeholders, translate complex requirements into technical solutions, and clearly communicate technical concepts to non-technical audiences. This role is heavily focused on data analysis, data engineering, and business-facing collaboration within a fast-paced Agile environment.
Key Responsibilities
- Analyze complex business requirements and translate them into scalable data solutions.
- Design, develop, and maintain data pipelines using Python, SQL, BigQuery, and Google Cloud Platform (GCP) technologies.
- Create and modify business logic using Python-based data processing frameworks.
- Develop and support data workflows orchestrated through Airflow Composer.
- Work with enterprise datasets stored within GCP Enterprise Data Platform (EDP) environments.
- Consume and integrate data from multiple source systems, including payer data and Epic datasets.
- Validate and reconcile data against legacy SQL Server environments during migration and modernization initiatives.
- Partner directly with business stakeholders to understand reporting, analytics, and operational data needs.
- Document business requirements, data logic, transformations, and technical solutions.
- Troubleshoot data quality, transformation, and pipeline issues across cloud and legacy environments.
- Collaborate within an Agile sprint model, managing work through GitHub and leveraging AI-assisted development tools such as Claude.
- Communicate findings, technical recommendations, and project updates effectively to both technical and non-technical audiences.