ETL Python Developer || Hybrid || W2 role

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

Python Developer
ETL/data integration
Pandas
NumPy
PySpark
AWS
Azure
GCP
SQL

Job Details

Role: ETL Python Developer

Location: Charlotte, NC (Day 1 Hybrid – 3 days office in a week)

Contract -W2 . H1b transfers are accepted.

 

Job Description:

We are looking for a highly experienced ETL Python Developer with over 8+ years of expertise in designing, developing, and maintaining robust data pipelines and ETL workflows. The ideal candidate will have a strong background in Python programming, data integration, and processing large-scale datasets to support analytics and business intelligence initiatives.

 

Key Responsibilities:

  • Design, develop, and optimize scalable ETL processes and data pipelines using Python.
  • Build robust data workflows for extracting, transforming, and loading data from various sources to data warehouses or lakes.
  • Collaborate with data analysts, data engineers, and stakeholders to understand data requirements.
  • Implement data quality checks and validation mechanisms within ETL workflows.
  • Automate data ingestion, transformation, and reporting processes for efficiency and accuracy.
  • Monitor, troubleshoot, and optimize existing ETL processes for performance and reliability.
  • Maintain documentation of ETL processes, data flow diagrams, and technical specifications.
  • Adhere to best practices for coding, version control, and deployment.

 

Required Skills & Experience:

  • 8+ years of professional experience in Python development, with a focus on ETL/data integration.
  • Strong proficiency in Python, including libraries such as Pandas, NumPy, PySpark, or similar.
  • Hands-on experience with building and maintaining large-scale ETL workflows.
  • Familiarity with data warehousing solutions (e.g., Amazon Redshift, Snowflake, Teradata, etc.).
  • Experience working with databases (SQL and NoSQL), including complex querying and data modeling.
  • Knowledge of cloud platforms (AWS, Azure, Google Cloud Platform) and cloud data services is a plus.
  • Experience with workflow orchestration tools such as Apache Airflow, Luigi, or similar.
  • Strong problem-solving skills and attention to detail.
  • Excellent communication and teamwork abilities.

 

Preferred Qualifications:

  • Experience with big data technologies (Spark, Hadoop) is advantageous.
  • Familiarity with DevOps practices for deploying and scheduling ETL jobs.
  • Knowledge of data governance and security best practices.
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