Principal, Data Analytics and Engineering

bluemercury•New York, NY

4d•$163,800 - $272,760

About The Position

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.

Requirements

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.

Nice To Haves

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.
Master’s degree and relevant professional certifications preferred.

Responsibilities

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.
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.
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.
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.
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.
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.