Senior Data Engineer - PySpark, AWS ETL & Pipelines

Talentify; Charlotte (NC); On-site; USD 120,000 - 180,000; Full time

Job summary

Talentify seeks a Sr Data Engineer to join a data team focused on building scalable data integration and ETL pipelines. You will design and develop data/batch processing using Python, PySpark, and AWS services to deliver business value and support analytics across large data domains.

You will collaborate with business areas to define requirements, document designs, and implement robust solutions while adhering to SDLC and DevOps practices.

Qualifications

• Hands-on data engineering with Python and PySpark
• Experience with AWS services (Glue, Lambda, S3, RDS, MSK, Step Functions)
• Strong SQL and relational database skills (Postgres, SQL Server)
• Proficiency in design and development of ETL pipelines
• Experience with REST APIs and data integration patterns
• Familiarity with UNIX scripting and data modelling techniques

Responsibilities

• Provide scoping, estimating, planning, design, development and support for projects
• Develop and maintain ETL pipelines for large data domains
• Design data integration solutions using Python/PySpark and AWS services
• Document technical designs and present alternatives to clients
• Collaborate with analysts to prioritize requirements
• Follow SDLC processes and ensure quality and defect tracking
• Coordinate vendors and contractors as needed
• Stay updated on industry best practices and trends

Skills

Python

PySpark

AWS

ETL Development

SQL

Data Engineering

Unix scripts

REST APIs

CI/CD DevOps

GitHub

Jenkins

Agile/SCRUM

Data modeling

Tools

Control-M

Autosys

GitHub

Jenkins

Job description

Talentify seeks a Sr Data Engineer to join a data team focused on building scalable data integration and ETL pipelines. You will design and develop data/batch processing using Python, PySpark, and AWS services to deliver business value and support analytics across large data domains.

You will collaborate with business areas to define requirements, document designs, and implement robust solutions while adhering to SDLC and DevOps practices.