Title: Data Analytics Consultant
Location: Washington, D.C.
Job Type: Contract
Work Type: Hybrid (Need to go to the office once in a week)
Travel: Up to 25%
Technical Skills:
Skill | Years/Level of Experience |
Data Virtualization | 3 to 5 years |
Data Engineering | 3 to 5 years |
Statistical Analysis | 3 to 5 years |
Python (Programming Language) | 3 to 5 years |
Azure Synapse Analytics | 3 to 5 years |
Role Description:
The Data Analytics Consultant to help clients harness data to improve business performance and drive strategic outcomes. In this role, you will analyze large datasets, build dashboards, and translate insights into clear, actionable recommendations. You will collaborate with crossfunctional teams to define requirements, develop data models, and deliver analytics solutions that support decisionmaking. The ideal candidate brings strong problemsolving abilities, excellent communication skills, and experience with modern analytics tools. This position offers opportunities to innovate, influence client strategy, and support continuous improvement across analytics practices.
· 3–7 years of experience in analytics, BI, or consulting (adjust years based on level).
· Demonstrated success leading analytics projects from scoping to delivery and adoption.
· Strong command of data modeling, SQL, and visualization best practices.
· Experience advising stakeholders and influencing decisions with evidence-based insights.
· Data Visualization: Power BI, Tableau, Looker (design systems, DAX/LOD, performance tuning).
· Data Engineering (light): SQL (joins, window functions, CTEs), ETL/ELT workflows, data warehousing concepts.
· Analytics: Statistical analysis (regression, time-series, clustering), experiment design, forecasting, scenario modeling.
· Programming (preferred): Python (pandas, NumPy, scikit-learn), or R (tidyverse).
· Cloud & Data Platforms (preferred): Azure (Synapse, Fabric), AWS (Redshift, Athena), Google Cloud Platform (BigQuery), Snowflake, Databricks.
Education Level: Bachelor’s or Master’s in Data Analytics, Statistics, Computer Science, Information Systems, Economics, or related field.
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