Data Analyst

Lorvenk Technologies LLC
Virginia Beach, VA, United States
2 days ago
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Role details

Contract type
Contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Data Analysis Computer Programming Information Engineering Data Infrastructure Github Python (Programming Language) SQL Databases Scripting GitHub Copilot Snowflake
+6 more
AWS Data Analytics Data Management Claude Software Version Control Data Pipelines Databricks

Job description

Data engineer or Analyst - mix of both is good In general he wants a combination of both skill sets Some will be working on data engineer Mainly looking for technical skills- Python, scripting, databricks AI tools Python AWS Cloud how to work with AWS Data engineering SQL Snowflake -already have people with this experience Databricks -important -Both important but if they are better at one than other that is ok Mainly scripting, data management, automation Exposure to Claude is good- team will be using this heavily Financial services background- any industry will be ok No strong restriction on previous migration experience Exposure to Claude is good Will be looking for active migration Need to change their process to consume to newer sources Data validations Experience level: 5-6 years

Independent Ownership: Manage the full lifecycle of data projects-from gathering requirements with Product and Process partners to executing technical solutions and presenting outcomes to leadership. Data Engineering & Platform Enablement: Build, maintain, and scale robust data pipelines and analytical data products specifically tailored for the Card LOB. Controls Modernization & Risk Management: Leverage enterprise and industry technologies to modernize business and regulatory controls, ensuring operational excellence and transparency. Strategic Initiatives: Contribute to high-impact, complex initiatives including data infrastructure modernization, Discover integration, and the convergence toward enterprise data products. AI-First Innovation: Utilize AI-assisted development tools and methodologies to accelerate coding, data curation, and analytical workflows. Collaborative Environment: Participate in stand-ups, knowledge-sharing sessions, and dedicated collaboration channels. Work daily with modern data and AI technologies (with comprehensive training provided for enterprise-specific platforms): Core Languages & Platforms: SQL, Snowflake, Databricks, Python Version Control & Collaboration: GitHub AI Development Tools: GitHub Copilot, Claude Enterprise Platforms: eDQ, EMP, Snowland, Skycap (Capital One Specifc)

Requirements

Analytical & Coding Proficiency: Strong foundation in data analysis and programming (SQL/Python) with a drive to master new enterprise tools. AI-First Mindset: Enthusiasm for integrating generative AI tools and modern methodologies into daily engineering and analytical workflows. Business & Domain Curiosity: Ability to quickly grasp complex business contexts and translate ambiguous requirements into well-documented technical solutions. Ownership & Communication: High degree of independent problem-solving paired with strong written and verbal communication skills to engage stakeholders and leadership effectively.

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