Data Analyst

Overview

Job Overview:

We are seeking a highly skilled Data Engineer on a consulting basis to help optimize and scale our data infrastructure for apparel production, sales forecasting, and customer insights. The ideal candidate will have expertise in data modeling, ETL processes, and cloud-based analytics, ensuring that data-driven decisions enhance business efficiency and growth.

Key Responsibilities:

Data Infrastructure & Management:

Design and implement scalable data pipelines for apparel inventory, supply chain, and customer analytics.

Develop and maintain data warehouses and real-time analytics platforms.

Optimize ETL processes for efficient data ingestion, processing, and storage.

Ensure data integrity, security, and compliance with industry standards.

Business & Market Insights:

Collaborate with merchandising, marketing, and operations teams to extract actionable insights.

Implement predictive models for demand forecasting and trend analysis in apparel sales.

Improve customer profiling using data-driven segmentation and personalization strategies.

Technology & Tools:

Work with SQL, Python, Apache Spark, or other big data technologies.

Utilize cloud platforms such as AWS, Azure, or Google Cloud for data architecture.

Integrate AI/ML models for data-driven product recommendations and business insights.

Provide recommendations for optimizing business intelligence dashboards (Power BI, Tableau, Looker, etc.).

Skills & Qualifications:

Bachelor's or Master’s degree in Computer Science, Data Science, or a related field.

Proven experience in data engineering, ETL development, and database management.

Strong understanding of apparel industry data trends, including supply chain, inventory management, and consumer behavior.

Expertise in cloud computing technologies (AWS, Azure, GCP).

Ability to work independently and provide strategic data insights to stakeholders.

Excellent communication and problem-solving skills.

Contract Details & Expectations:

Work closely with internal teams to identify key data challenges and opportunities.

Deliver actionable insights and implement scalable data solutions.

Flexible working hours, with periodic check-ins and progress reports.

Possibility of transitioning into a full-time role based on performance and business needs.

Job Type: Part-time

Supplemental Pay:

• Overtime pay
• Performance bonus
• Yearly bonus

Work Location: In person