Data Analyst II

Position Summary

The Data Engineer / Analytics Engineer II is responsible for designing, building, and maintaining scalable data infrastructure and data products that enable commercial analytics and data-driven decision-making.

This role bridges business and technology, transforming complex, multi-source commercial data into reliable, high-performance data models, pipelines, and data marts that support reporting, analytics, and data science initiatives. This position will have to be flexible to work the US hours.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain scalable data pipelines for structured and unstructured commercial data
• Develop and optimize ETL/ELT processes using Python, SQL, and orchestration tools (e.g., Airflow)
• Automate data workflows and integrations across sales, finance, pricing, and operational systems
• Drive integration of ChatGPT and LLM activities through scalable prompt-driven development workflows, and operationalizing AI-assisted engineering projects

Data Architecture & Modeling

• Design and implement data marts and scalable data architectures
• Apply dimensional modeling techniques (star, snowflake schemas)
• Ensure data models are optimized for performance, usability, and scalability

Data Integration & Systems

• Integrate data from CRM systems, financial systems, and other enterprise platforms
• Develop APIs and data services to enable downstream consumption
• Ensure data consistency, governance, and quality across platforms

Analytics Enablement

• Partner with analysts and data scientists to deliver clean, reliable datasets
• Support Power BI/Tableau reporting infrastructure (datasets, dataflows, DAX)
• Enable self-service analytics through well-structured data layers

Advanced Analytics & Data Science Support

• Support or lead advanced analytics initiatives, including predictive modeling
• Perform advanced data analysis using Python and related libraries
• Translate business requirements into scalable technical solutions

Project & Stakeholder Management

• Lead complex data projects from design through delivery
• Collaborate with IT, sales, finance, and analytics teams
• Balance ad hoc requests with long-term platform development

Day-to-Day Activities

• Build and maintain data pipelines and workflows
• Write and optimize complex SQL queries
• Design and evolve data models and data marts
• Troubleshoot data issues across systems and dashboards
• Collaborate with stakeholders to translate requirements into scalable data solutions

Required Qualifications

• 4–5+ years of experience in data engineering or analytics engineering
• Strong proficiency in:
  • SQL (advanced queries, performance tuning)
  • Python (data processing, automation)
• Experience with:
  • Data warehousing (e.g., Redshift, AWS)