Sr. Pyspark developer with spark streaming and AWS

Overview

Remote
$40 - $50
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

API
Agile
Amazon EKS
Amazon S3
Amazon Web Services
Apache Airflow
Apache HTTP Server
Apache NiFi
Apache Spark
Communication
Continuous Delivery
Continuous Improvement
Continuous Integration
Customer Facing
Data Analysis
Data Engineering
Data Extraction
Data Flow
Data Governance
Docker
Electronic Health Record (EHR)
FOCUS
Innovation
Kubernetes
Management
Performance Tuning
PostgreSQL
PySpark
Python
RESTful
Real-time
Streaming
Telecommunications
Transact-SQL
Workflow
aws

Job Details

The ideal candidate will have deep expertise in building scalable data pipelines using PySpark and Spark Streaming, along with experience working on modern AWS-based data platforms. This role requires strong consulting and communication skills, a passion for innovation, and the ability to work independently in a fast-paced, client-facing environment.
Telecommunications industry experience is highly preferred.

Key Responsibilities:
  • Design and develop scalable data pipelines using PySpark and Spark Streaming
  • Implement data workflows on AWS EMR, orchestrated via Apache Airflow
  • Deploy and manage streaming applications on Amazon EKS with Spark Streams
  • Integrate and manage data flows using Apache NiFi
  • Work with Apache Iceberg tables stored in Amazon S3
  • Enable data access via AWS Aurora PostgreSQL for downstream API consumption
  • Write and optimize complex T-SQL queries for data extraction and transformation
  • Identify and implement improvements in pipeline performance, resource tuning, and automation
  • Drive innovation by streamlining workflows and increasing automation
  • Collaborate with cross-functional teams and clients to deliver high-quality data solutions
  • Participate in code reviews, architectural discussions, and performance tuning sessions
  • Independently manage priorities and deliverables in a dynamic, agile environment

Required Skills & Qualifications:
  • 5+ years of experience in data engineering with a strong focus on PySpark
  • Proficient in Spark Streaming and real-time data processing
  • Hands-on experience with AWS EMR, Apache Airflow, and Amazon EKS
  • Strong skills with Apache NiFi for data ingestion and transformation
  • Experience working with Apache Iceberg tables and S3-based data lakes
  • Solid understanding of AWS Aurora PostgreSQL and REST API integration
  • Proficient in T-SQL, Python, and SQL
  • Demonstrated expertise in performance tuning for distributed data pipelines
  • Previous experience in client-facing roles or consulting environments
  • Strong verbal and written communication skills
  • Self-starter with a passion for innovation, continuous improvement, and problem-solving

Preferred Qualifications:
  • AWS Certification (e.g., AWS Certified Data Analytics Specialty)
  • Experience with CI/CD pipelines and containerization (Docker, Kubernetes)
  • Familiarity with data governance and security best practices
  • Telecommunications industry experience is a strong plus

To apply, please send your updated resume to:
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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