Senior Data Engineer-CW

Job Description: This role is an integral senior member of a technical team, responsible for supporting the design, development, and maintenance of the organization's data infrastructure, ensuring the efficient and reliable flow of data across various systems. At least 5 years using: API, SFTP, and Kafka-based data pipelines, ETL/ELT development, data modeling, performance optimization, data quality, automation, and scalable cloud-native data architecture.

Job Title: Senior Data Engineer
Duration: 12 Months (Possible Contract to Hire)
Location: 100% Remote

Additional Comments:

Client has requested more candidates immediately with the following skills/experience :

JAVA

Smile CDR

EHR data implemantation (Athena, Epic, Cerner/Oracle, Veradigm)

The manager wants these candidates shortlisted to him immediately and they will likely be interviewed

Job Description:

• This role is an integral senior member of a technical team, responsible for supporting the design, development, and maintenance of the organization's data infrastructure, ensuring the efficient and reliable flow of data across various systems.
• This position is responsible for ensuring the reliable movement, transformation, and storage of data across various platforms. The incumbent will work closely with data professionals, analysts, and engineers to build and optimize data pipelines, ensuring data quality and integrity.
• The ideal candidate is adaptable, solution-oriented, and capable of collaborating across multiple teams to support a broad range of data initiatives.
• The incumbent and team will be involved in every aspect of the data process, from idea generation, analysis, design, build, and support, using the latest technologies and design patterns.

Required Qualifications:

• 7-10 years as a Data Engineer with experience designing and supporting healthcare data platforms and integrations
• 7-10 years using Google Cloud Platform (GCP),

Preferred Qualifications:

• At least 5 years using : Dataproc, Data Composer, BigLake, BigQuery, Iceberg, Starburst, dbt, and PySpark.
• At least 5 years using : API, SFTP, and Kafka-based data pipelines, ETL/ELT development, data modeling, performance optimization, data quality, automation, and scalable cloud-native data architecture.