Data Analyst - Senior

Description

Enterprise data engineering and SQL Strong ability to source, join, transform, validate, and document data across large enterprise platforms like Snowflake, Palantir, Databricks, and SQL-based warehouses.


Data quality troubleshooting and root cause analysis Ability to investigate discrepancies, missing data, duplicates, mapping issues, refresh problems, and transformation failures - then define sustainable remediation steps. Data requirements mapping Skill in translating business needs into source-to-target mappings, field definitions, business rules, data models, validation criteria, and technical specifications

AI/agent data enablement Ability to prepare trusted, structured, business-ready datasets for Copilot Studio agents, Microsoft Copilot, Databricks AI/BI, dashboards, retrieval, and workflow automation.


Cross-functional communication and collaboration Ability to work with developers, business stakeholders, data owners, transformation partners, and platform teams while explaining technical data topics clearly to non-technical audiences.

Data Analyst Senior Roles and Responsibilities include, but are not limited to:


1) Conducting full lifecycle analysis to include requirements, activities and design.


2) Data Analysts will develop analysis and reporting capabilities.


3) Monitor performance and quality control plans to identify improvements.


4) Ability to turn project requirements into custom-formatted data reports.


5) Able complete life cycle data generation and outline critical information for each Project Manager.


6) Able to analyze business procedures and recommend specific types of data that can be used to improve upon them.


7) Create a prioritized list of needs for each business segment and area of focus.


8) Identify and recommend new ways to save money by streamlining processes.


9) Work with managers to outline the specific data needs for business method analysis project.