Hi
Greeting for the day
I'm trying to ask you regarding the job opening. Please find the below job description. Fill the below details, Attach your DL, Visa copies as soon as possible. It’s a fast moving position.
Candidate Submission Details
| Submission Details | |
| Candidate Full Name as per the Passport: | 
 | 
| Phone Number: | 
 | 
| Email Id: | 
 | 
| Alternate Number: | 
 | 
| Alternate Email ID: | 
 | 
| Skype ID: | 
 | 
| Current Location: (Complete Address) | 
 | 
| Open for Relocation across USA (Yes/No): | 
 | 
| Work Authorization (Visa Status): | 
 | 
| Last 4 Digit SSN: | 
 | 
| DOB (MM/DD): | 
 | 
| Total Onsite Experience, Working in USA: | 
 | 
| Overall Relevant Experience of the Candidate: | 
 | 
| Availability for Skype Interview: | 
 | 
| Availability for New Project: | 
 | 
| LinkedIn URL: | 
 | 
| in which year LinkedIn created: | 
 | 
| Passport No (Must): | 
 | 
| In which year came to US: | 
 | 
| On which visa came to US: | 
 | 
| Highest Education qualification (Course / College / University / Year of Passing): | 
 | 
| Any offers in Pipeline: | 
 | 
| 2 References: | 
 | 
| Employer Details (name, email id, phone no, company name): | 
 | 
AR: 520952
Job Title: Python Developer with heavy ETL, Pandas, NumPy, SQL)
Location: McLean, VA
Job Type: Full-Time / Contract
Onsite/Hybrid : 5 Days Onsite
Experience: 8+ years total. Data Lake is desirable
Job Description
Required Skills
Strong programming experience in Python.
Proficiency in Pandas, NumPy, and working with SQL queries.
Experience working with Data Lake and processing large volumes of data.
Ability to parse and consolidate data from Excel, CSV, and plain text formats.
Hands-on experience in writing unit tests, performing regression testing, and implementing error/exception handling.
Key Responsibilities
Write effective Python code for data extraction, transformation, and loading (ETL).
Perform data manipulation and analysis using Pandas, NumPy, and SQL.
Work with structured and unstructured data sources (Excel, CSV, text files) from a Data Lake environment.
Implement robust error handling and exception handling in Python scripts.
Develop and maintain unit tests and regression tests to ensure data accuracy and code stability.
Collaborate with data engineers, analysts, and business teams to gather requirements and deliver data solutions.
Optimize and refactor existing code for better performance and scalability.
| 
 |