Data Engineer with PowerBI and Python_Only W2 // NO C2C //

Overview

Hybrid
$60 - $70
Contract - W2
Contract - 12 Month(s)

Skills

API
Amazon Web Services
Authorization
Cloud Computing
Dashboard
Data Analysis
Data Engineering
Data Governance
Data Management
Data Manipulation
Data Quality
Data Visualization
Data Warehouse
Database
Debugging
Decision-making
Enterprise Architecture
Google Cloud
Google Cloud Platform
Microsoft Azure
Microsoft Power BI
NoSQL
NumPy
Pandas
Project Scoping
Python
SQL
Scripting
TOGAF
Writing
Zachman Framework

Job Details

Job Title: Data Engineer

Work Authorization: W2

Location: Concord, CA (preferred), Charlotte, Iselin, NJ

Project Scope:

We are looking for a data engineer to help out with an enterprise architecture organization. we are looking someone who has PowerBI, strong Python experience and strong data management and data analysis background. This will help us with the analysis toward the enterprise architecture.

Project Scope:

We are seeking a highly skilled and motivated Data Engineer to join our Enterprise Architecture organization. In this critical role, you will leverage your expertise in data engineering to drive insightful analysis that informs and shapes our enterprise architecture strategy. You will be instrumental in transforming raw data into actionable intelligence, enabling better decision-making across the organization.

Day-to-Day Responsibilities:

Building and optimizing data pipelines.

Developing and refining PowerBI reports and dashboards.

Writing and debugging Python scripts for data manipulation and analysis.

Collaborating with enterprise architects on data requirements and analysis.

Troubleshooting data-related issues.

Performing ad-hoc data analysis to support ongoing projects.

Must-Have Skills:

Experience in PowerBI: Demonstrated experience in developing complex dashboards, reports, and data models.

Experience in Python: Expertise in data manipulation, scripting, and automation (e.g., pandas, NumPy, SQL libraries).

Strong data management background: Solid understanding of data warehousing, database concepts (SQL/NoSQL), data governance, and data quality principles.

Strong data analysis background: Proven ability to analyze large datasets, identify trends, draw conclusions, and present findings effectively.

Increased technical depth, particularly in Python and PowerBI.

Preferred Qualifications (Optional, consider adding if relevant):

Experience with cloud data platforms (e.g., Azure Data Factory, AWS Glue, Google Cloud Platform).

Familiarity with enterprise architecture frameworks (e.g., TOGAF, Zachman).

Experience with other data visualization tools.

Understanding of API integrations for data extraction

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