Senior Data Analyst / Engineer with Azure, Power BI, Python

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 12 Month(s)

Skills

Analytics
Data Analysis
Dashboard
Data Governance
Data Modeling
Data Processing
Microsoft Power BI
Python

Job Details

We are seeking a Mid-level to Senior Data Science Consultant to support data cleanup, analytics, and governance initiatives for vertical asset data. The consultant will play a key role in ensuring data accuracy, consistency, and quality by leveraging analytics, automation, and visualization tools.

This position requires a blend of technical proficiency, analytical thinking, and strong communication skills to collaborate with cross-functional teams and data owners.

Key Responsibilities

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  • Utilize advanced analytics techniques to automate the correction of asset attribute data for records already in the database.

  • Develop and execute queries and scripts to identify and replace incorrect or missing data attributes based on asset Type, Class, and related fields.

  • Produce, test, and run code to query specific fields or character strings and apply data corrections efficiently.

  • Design and implement a Power BI dashboard to highlight data quality issues and enable Asset System Managers (ASMs) to monitor and prioritize improvements.

 

  • Contribute to the development and review of data governance processes and data standards for vertical assets.

  • Conduct comprehensive analysis of data integrity within the TEAMS system and document findings through clear reports, visuals, and memos.

  • Collaborate with data owners to verify, correct, and enhance data accuracy.

  • Identify and recommend process improvement opportunities based on data-driven insights.

  • Develop tools and scripts in SAS or other approved software (Python, Azure tools, etc.) for continuous data quality monitoring.

  • Provide documentation, process maps, and training to WSSC staff to ensure sustainability of data governance practices.

Required Skills & Experience

  • 5- 10 years of experience in Data Science, Data Engineering, or Data Analytics roles.

  • Proficiency in:

    • SQL (complex queries, data manipulation, and optimization)

    • Power BI (dashboard creation, DAX, and data modeling)

    • Python or other scripting languages (for automation and data processing)

    • Azure Data Services (Data Factory, Synapse, or related tools)

  • Experience working with multiple data sources, including structured and unstructured data.

  • Strong understanding of data governance principles, metadata management, and data quality frameworks.

  • Excellent analytical, documentation, and communication skills to present findings to both technical and non-technical audiences.

Preferred Qualifications

  • Experience working with utility or public sector asset management systems (e.g., TEAMS).

  • Knowledge of data standards and governance frameworks for asset-intensive organizations.

  • Hands-on experience with data quality and cleansing automation techniques.

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.