Principal, Data Analytics and Engineering

Description

About Bluemercury:

With 178 locations across the country and growing, Bluemercury pioneered a client-first service model that emphasizes hyper-personalized, high-quality beauty interactions. The leading luxury beauty destination and Macy’s, Inc. nameplate offers a highly curated and premium product assortment across a range of categories, Bluemercury helps people discover their unique self by shining a light on what makes them wonderfully distinctive. As Bluemercury continues to evolve, it remains committed to its original intent to serve people and embrace its purpose to be the ultimate specialist in the beauty of every individual. For more information, please visit www.bluemercury.com.

Job Overview:

The Principal Engineer, Data & Analytics Engineering, is Bluemercury’s senior hands-on technical leader responsible for architecting, building, and scaling our enterprise data ecosystem. This role blends deep engineering expertise with technical leadership – driving architecture decisions while remaining actively involved in coding, designing, troubleshooting, and optimizing mission-critical pipelines and platforms. You will partner closely with product, engineering, and business stakeholders to ensure our data foundations are robust, secure, and built for long-term growth.

Key Responsibilities:

• Hands-On Data Platform Engineering & Architecture
• Design, build, and directly contribute code to scalable data platforms on Google Cloud Platform (GCP).
• Lead hands-on engineering of Snowflake: schema design, performance tuning, resource optimization, and governance.
• Implement CI/CD pipelines, monitoring, logging, testing frameworks, and data quality automation.
• Serve as the primary technical expert for data reliability, platform performance, and architectural decision-making.

• Semantic Layer & Enterprise Reporting Enablement
• Architect and implement the AtScale semantic layer solutions, including aggregates, metrics, and performance optimizations.
• Provide hands-on technical support for Tableau data sources, extracts, and performance tuning.
• Establish patterns that ensure accurate, consistent, and trusted enterprise reporting.

• Integration Engineering & Data Pipelines
• Develop and optimize complex data flows using Workato, GCP services, and custom code.
• Build scalable ingestion frameworks for batch and streaming data.
• Troubleshoot and resolve pipeline issues at the system, code, and infrastructure levels.

• Customer Data Platform Engineering
• Provide hands-on ownership of the Amperity CDP, including identity resolution logic, profile stitching, segmentation workflows, and system integrations.
• Integrate and engineer data enrichment workflows with Bridg and other append platforms.
• Ensure data structures and pipelines enable advanced personalization and CRM activation.

• Enablement of Data Science & Advanced Analytics
• Engineer production-ready data products, feature sets, and ML-ready datasets.
• Build and operationalize model scoring pipelines in partnership with data science teams.
• Maintain documentation, lineage, and metadata standards for transparent analytics operations.

• Technical Leadership & Influence
• Set engineering standards through direct contribution and technical excellence.
• Conduct design reviews, propose architecture patterns, and drive platform evolution.
• Mentor engineers across data engineering, analytics engineering, and integrations—acting as the senior technical resource.
• Influence roadmaps and cross-functional decisions using hands-on insights and deep platform understanding.

Qualifications:

• Required
• 10+ years in data and analytics engineering or multi-tier analytics platform architecture, with significant hands-on engineering experience.
• Expert with:
• GCP (GCS, Compute, storage optimization)
• Snowflake performance engineering
• AtScale semantic modeling
• Workato, Airflow, or similar orchestration tools
• Amperity or similar CDPs
• Advanced SQL, Python, and data modeling skills (dimensional, 3NF, Data Vault).
• Deep experience engineering large-scale retail or consumer datasets.

Preferred

• Experience designing ML feature stores and production-grade data science pipelines.
• Proven ability to lead architecture through hands-on contributions.
• Retail industry experience.
• Experience of integrating data platform with ERP and POS solutions in mid to large organizations.
• Excellent leadership, communication, and stakeholder management skills.
• Strong analytical, troubleshooting, and solution architecture skills.
• Excellent communication and stakeholder engagement abilities.

• What Success Looks Like
• You model engineering excellence and deliver high-quality, efficient, hands-on solutions.
• The enterprise data platform is stable, scalable, cost-efficient, and trusted.
• Pipelines, workflows, and semantic layers are fully automated, monitored, and documented.
• Customer data is accurate, unified, and actionable across the business.
• Engineering teams adopt your standards and accelerate their delivery effectiveness.

• Education
• Bachelor’s degree in Computer Science, Information Systems, Computer Science, Engineering, or a related field, or demonstrated equivalent experience in a technical role. (required).
• Master’s degree and relevant professional certifications preferred.

• This job description is not all inclusive. Bluemercury, Inc. reserves the right to amend this job description at any time. Bluemercury, Inc. is an Equal Opportunity Employer, committed to a diverse and inclusive work environment.
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