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Data Engineer

People Trust -
Desde casa

Postulación rápida

Información del empleo

Tiempo completo
$35,000 a $45,000 por mes

Cualificaciones

Modelado de datos
Azure
Informática
Big data
DevOps
Spark
Microsoft SQL Server
Sin necesidad de experiencia
Sistemas de información
Java
Experiencia en bases de datos
SQL
Licenciatura
JavaScript
Seguridad
Apache
Kafka
SSIS

Descripción completa del empleo

Position Title: Data Engineer

Client Company: Ascend Learning

Location: Remote (Work@Home)

Schedule: 9:00 am to 6:00 pm CST, M-F except for USA National Holidays

Duration: Full-Time

Company Background:

A leading provider of technology-based educational, curriculum, and assessment solutions for the healthcare industry and other vocational fields. Renowned for delivering solutions that result in higher-performing student results at a lower cost, from nursing to allied health and fitness training to OSHA compliance training and insurance. Employs more than 900 employees in 35 states. Customers range from schools of nursing to institutions of higher education, corporate health, and wellness organizations, and major Fortune 500 insurance companies.

Position Summary:

We are seeking a highly skilled and detail-oriented Data Engineer to join our data team. This role is focused on designing, building, and optimizing scalable data pipelines and data warehousing solutions. The ideal candidate will have strong experience in ETL processes, real-time data streaming, and cloud-based data platforms, ensuring that data is accurate, reliable, and accessible across the organization.

This position plays a critical role in supporting business intelligence, analytics, and data-driven decision-making initiatives.

Responsibilities:

Design, build, and maintain robust, scalable, and secure data pipelines and data workflows.
Develop and manage ETL/ELT processes for ingesting, transforming, and loading data from multiple sources (databases, APIs, cloud services, and third-party systems).
Build and optimize data integration solutions using tools such as Azure Data Factory, SSIS, and Kafka.
Implement real-time and batch data processing solutions, leveraging Kafka and streaming technologies.
Design, develop, and optimize data warehouse solutions, including schema design and data modeling.
Collaborate with data analysts, data scientists, and business stakeholders to translate data requirements into scalable technical solutions.
Optimize data architecture for performance, scalability, and reliability across cloud environments.
Ensure data quality, consistency, and integrity through validation, monitoring, and cleansing processes.
Work with RESTful APIs to enable seamless system and data integrations.
Maintain comprehensive documentation of data flows, architectures, and operational procedures.
Implement and adhere to best practices in data governance, security, and compliance.

Required Skills & Experience:

6+ years of experience in a data engineering role with a strong focus on data warehousing and ETL processes.
Strong expertise in SQL Server and Snowflake, including data modeling, complex SQL development, and performance tuning.
Hands-on experience building ETL pipelines using Azure Data Factory, SSIS, and Kafka.
Strong experience with real-time data processing and streaming technologies, particularly Kafka.
Solid understanding of data warehouse design, data modeling, and database best practices.
Proficiency in Java for scripting and automating data workflows.
Hands-on experience with Azure Cloud Services, including Azure Data Factory and Azure SQL Database.
Experience integrating systems using RESTful APIs.
Strong understanding of cloud infrastructure, automation, and security best practices.
Ability to work with large-scale datasets and optimize data processing workflows.
Strong analytical and problem-solving skills with high attention to detail.
Excellent communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field—or equivalent practical experience.

Desired Skills & Experience (Not required but considered a plus):

Experience with additional data orchestration tools such as Apache NiFi or Prefect.
Familiarity with big data processing frameworks (e.g., Apache Spark).
Knowledge of data governance, privacy regulations (e.g., GDPR), and compliance standards.
Exposure to DevOps practices and Infrastructure as Code (IaC).
Relevant cloud or data engineering certifications.

Job Type: Full-time

Pay: $35,000.00 - $45,000.00 per month

Education:

Bachelor's (Required)

Experience:

Data Engineering: 6 years (Required)
SQL Server and Snowflake: 6 years (Required)
Kafka: 6 years (Required)
Java: 3 years (Required)
integrating systems using RESTful APIs: 1 year (Required)

Work Location: Remote

Postulación rápida

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