Job DescriptionJob 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.TECH00
