Tiger Analytics Inc. Verified

Information Technology & Services, Management Consulting, Analytics, Artificial Intelligence

Data Analyst

Richmond, Virginia, United StatesHybridContractPosted 2 months agoVisa sponsorship available

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Role summary

This Data Analyst role focuses on extracting business insights from data, building dashboards, and developing automated data pipelines. The analyst will be responsible for managing data quality, including metadata and lineage, and troubleshooting existing data solutions. Key responsibilities include communicating with stakeholders to understand business requirements, independently writing Snowflake queries, and leveraging Python for automated data processes. The role also involves partnering with the business to provide consultancy, translate needs into data tools and metrics, and drive data analysis for strategic insights. Familiarity with AWS and Spark is preferred.

Job Title: Data Analyst

Location: Richmond/McLean, VA

Long term

Must have skills:

Proficient with SQL

Proficient with Python

Good soft and analytical skills

Nice-to-have skills:

AWS

Spark

Job Overview:

• Key Tasks: Analyze data for business insights, build dashboards, and develop automated production pipelines.

• Quality & Support: Manage data quality (lineage/metadata) and troubleshoot existing data solutions.

Job Description: Responsibilities:

Communicating with internal team and customers to understand data content and business requirements

Demonstrate ability to create and modify Snowflake queries independently

Strong Python data analytical skills to develop processes that are fully automated

Partner with the business to provide consultancy and translate the business needs to design and develop tools, techniques, metrics, and dashboards for insights and data visualization

Troubleshooting, debugging, maintaining and improving existing data sourcing and data solutions

Demonstrate ability to explore and quickly grasp new technologies to progress varied initiatives

Drive data analysis that provides meaningful insights on business strategies

Drive an understanding and adherence to the principles of data quality management including metadata, lineage, and business definitions

Build and execute production data pipelines and tools to monitor and report on data quality

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