Overview
Skills
Job Details
Job Title: Senior Alteryx Developer & Architect
Location: Charlotte, NC (Onsite)
Duration: 6 Months
Job Description:
We are seeking an experienced Alteryx Developer & Architect with a deep understanding of data analytics and process automation to drive high-impact financial data solutions.
You'll play a key role in designing and implementing Alteryx workflows for data ingestion, preparation, quality assurance, and regulatory report validation.
Key Responsibilities:
Platform Expertise: Leverage Alteryx capabilities, including Designer, Server, Intelligence Suite, and Alteryx Analytics Cloud, to develop and optimize ETL, data quality, and automation workflows.
Data Mastery: Lead data ingestion, preparation, and enrichment processes, ensuring the accuracy and reliability of foundational data elements.
Financial Compliance: Design and validate financial regulatory reporting solutions with a focus on high standards of data accuracy, governance, and compliance.
Quality Assurance: Implement quality checks and robust testing frameworks to ensure data integrity and consistent performance across analytics solutions.
Technical Leadership: Mentor junior team members, share best practices, and guide solution design using Alteryx, SQL, and Python.
Automation & Optimization: Drive automation initiatives for scalable and repeatable analytics using scripting and advanced Alteryx capabilities like Machine Learning, Location Intelligence, and Auto Insights.
Required Skills & Experience:
10+ Years in Data Analytics & Engineering with strong Alteryx expertise in both on-premises and cloud platforms.
Technical Proficiency: Advanced skills in Python and SQL for data manipulation, scripting, and automation.
Data Skills: Proficient in ETL processes, data preparation, data quality, and foundational data management principles.
Domain Knowledge: In-depth understanding of financial regulatory compliance and report validation processes.
Testing and QA Focus: Experience in developing testing frameworks and conducting rigorous data quality assessments for large datasets