Data Engineer

Overview

On Site
$55.20 - $61.76 hourly
Contract - W2
Contract - Temp

Skills

Advanced Analytics
Business Intelligence
Real-time
Data Integration
Extract
Transform
Load
ELT
Workflow
Collaboration
Analytics
Data Quality
Data-flow Diagrams
System Integration
Version Control
Data Engineering
Software Development
Apache Spark
Data Flow
Apache NiFi
Data Architecture
Performance Tuning
Python
PySpark
Data Processing
Amazon Web Services
Cloud Computing
Amazon S3
Electronic Health Record (EHR)
Amazon Redshift
Problem Solving
Conflict Resolution
Communication
Docker
Orchestration
Kubernetes
Apache HTTP Server
Continuous Integration
Continuous Delivery
Artificial Intelligence
Messaging

Job Details

RESPONSIBILITIES:
Kforce has a client that is seeking a Data Engineer in Maryland Heights, MO.

Summary:
We are seeking a skilled Data Engineer with a strong background in distributed data processing and cloud technologies. This role will be responsible for building and optimizing scalable data pipelines to support advanced analytics and business intelligence initiatives. The ideal candidate has hands-on experience working with Apache Spark, Python (PySpark), AWS cloud services, and Apache NiFi for real-time and batch data integration.

Responsibilities:
* Data Engineer will design, develop, and maintain scalable ETL/ELT pipelines using Spark and PySpark
* Implement and optimize data workflows using Apache NiFi for ingestion from multiple sources
* Work within the AWS ecosystem (e.g., S3, Lambda, EMR, Glue, Redshift) to build cloud-native data solutions
* Collaborate with data scientists, architects, and analysts to deliver high-quality data sets for analytics
* Monitor pipeline performance, troubleshoot issues, and ensure data quality and integrity
* As a Data Engineer, you will maintain and document data models, data flow diagrams, and system integration points
* Follow best practices in data engineering, including CI/CD, version control, and infrastructure as code

REQUIREMENTS:
* 5+ years of professional experience in data engineering or software development focused on data pipelines
* Hands-on experience with Apache Spark in large-scale data environments
* Experience designing and deploying data flows using Apache NiFi
* Strong understanding of data architecture, schema design, and performance tuning
* Strong proficiency in Python, specifically PySpark, for distributed data processing
* Proficient with AWS cloud services (e.g., S3, Glue, Lambda, EMR, Redshift)
* Excellent problem-solving and communication skills; ability to work in a fast-paced, team-oriented environment

Preferred Skills:
* Experience with containerization (e.g., Docker) and orchestration tools (e.g., Airflow, Kubernetes)
* Familiarity with Apache Iceberg or other modern table formats (e.g., Delta Lake, Hudi)
* Knowledge of CI/CD tools and practices for data infrastructure

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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