Senior Data Engineer - Spark & AWS

RESPONSIBILITIES:
Kforce has a client in the telecommunications industry that is seeking an experienced Senior Data Engineer in Greenwood Village, CO to join a high-impact engineering team developing enterprise-scale data solutions. This role offers the opportunity to work on modern cloud technologies, large-scale data processing, and AI-driven analytics that support mission-critical business initiatives. If you enjoy solving complex data challenges, building scalable data pipelines, and working with cutting-edge cloud and big data technologies, we'd love to hear from you.

Overview:
As a Data Engineer, you will build and optimize the data infrastructure that powers the platform's analytics capabilities. You'll design scalable data pipelines, develop distributed processing jobs, and ensure high-quality data is available to support AI-driven anomaly detection and advanced analytics. This role is ideal for engineers who enjoy working with large datasets, cloud technologies, and modern data engineering frameworks.

Responsibilities:
* Design, build, and maintain scalable data pipelines that ingest telemetry, log, and configuration data
* Develop distributed data processing applications using Apache Spark
* Build and optimize ETL/ELT workflows within a cloud-based data lake
* Collaborate with Data Scientists and AI Engineers to prepare and deliver data for analytics and machine learning workloads
* Optimize pipeline performance, scalability, and reliability
* Ensure data quality through monitoring, validation, and troubleshooting
* Partner with Platform Engineering to deploy and support data processing applications in AWS
* Contribute to data architecture decisions and engineering best practices

REQUIREMENTS:
* 5+ years of experience in Data Engineering or a related field
* Strong experience developing distributed processing applications with Apache Spark
* Experience with a second programming language such as Scala (preferred), Java, or another compiled language
* Experience designing and building scalable ETL/ELT pipelines
* Hands-on experience working with AWS cloud services
* Experience with cloud-based data lakes and large-scale datasets
* Strong understanding of distributed systems and data engineering best practices
* Proficiency in Python

Preferred Qualifications:
* Experience working with telemetry, log, or operational data
* Experience supporting AI, machine learning, or anomaly detection initiatives
* Experience working in Agile development environments
* Familiarity with streaming data technologies
* Knowledge of graph-based data models or network-related data

If you're passionate about building scalable data platforms and want to contribute to innovative cloud and AI initiatives within a leading telecommunications environment, we'd love to connect with you.

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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