Nextgen Invent Corporation

Senior Data Engineer

Vaga remota de Data Engineer com fit claro de localização do candidato.

Publicada24 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

Design, develop, and maintain scalable data pipelines and ETL/ELT workflows for structured and unstructured data.
Build and optimize data ingestion, transformation, and data integration processes using Python and Apache Spark.
Develop, schedule, and monitor workflows using Apache Airflow.
Design and manage enterprise data warehouse solutions using Amazon Redshift.
Implement data models, data marts, and reporting datasets to support analytics and business intelligence requirements.
Optimize data processing jobs and database performance for scalability and efficiency.
Work with large healthcare datasets, ensuring data accuracy, consistency, and compliance with industry standards.
Collaborate with business stakeholders to understand reporting and data requirements.
Implement data quality checks, validation frameworks, and monitoring processes.
Troubleshoot data pipeline issues and perform root cause analysis.
Ensure data security, governance, and compliance requirements are adhered to.
Participate in code reviews, development best practices, and continuous improvement initiatives.
Create and maintain technical documentation, data flow diagrams, and data mapping documents.
Work closely with cross-functional teams including Data Science, Analytics, Product, and Engineering teams.

6+ years of experience in Data Engineering, Big Data Engineering, or related roles.
Mandatory experience working in the Healthcare domain.
Strong hands-on experience in Python development for data engineering solutions.
Strong hands-on experience with Apache Spark (PySpark) for large-scale data processing.
Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
Strong experience designing, developing, and optimizing solutions on Amazon Redshift.
Advanced SQL skills with experience in query tuning and performance optimization.
Experience building ETL/ELT pipelines and modern data integration frameworks.
Strong understanding of data warehousing concepts, dimensional modelling, and data architecture.
Experience handling large-scale datasets and complex data transformation requirements.
Strong debugging, troubleshooting, and performance tuning skills.
Experience working with cloud-based data platforms and services (AWS or Azure) is preferred.
Excellent analytical and problem-solving skills.
Strong communication and stakeholder management capabilities.

Experience with AWS data services such as S3, Glue, EMR, Athena, Lambda, or Kinesis
Experience with Azure Data Factory, Azure Databricks, ADLS, Synapse Analytics, or other Azure data services
Exposure to Databricks, Snowflake, or modern Lakehouse architectures
Experience with CI/CD for Data Engineering pipelines
Knowledge of Healthcare data standards such as HL7, FHIR, EHR/EMR, Claims, Provider, Member, or Clinical Data
Experience with data governance, data quality, and compliance frameworks
Experience with Git and DevOps best practices for data engineering

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