Principal Data Engineer

BICP, a market leader in Decision Intelligence, enterprise modernization, and data-driven transformation, is seeking a highly experienced Principal Data Engineer to provide technical leadership and help advance a modern enterprise data platform for a rapidly growing company in the retail and performance-apparel industry.

This is a hands-on leadership role responsible for shaping data architecture, establishing engineering standards, and building scalable data solutions across Azure, Snowflake, Azure Data Factory, and Databricks. The Principal Data Engineer will collaborate with data engineers, architects, analytics teams, data scientists, product managers, and business stakeholders to deliver trusted data products that support analytics, reporting, machine learning, and AI.

The ideal candidate combines deep technical expertise with the ability to influence architecture, mentor engineers, and translate complex business requirements into scalable, production-ready solutions.

Key Responsibilities

• Provide technical leadership for the design and evolution of a modern, cloud-based enterprise data platform.
• Architect and develop scalable data pipelines using Azure Data Factory, Azure Databricks, Snowflake, Python, PySpark, and SQL.
• Establish reusable engineering patterns for data ingestion, transformation, orchestration, modeling, testing, deployment, and monitoring.
• Design batch and near-real-time integrations across enterprise applications, APIs, cloud platforms, and third-party data sources.
• Develop curated data products that support enterprise reporting, self-service analytics, data science, machine learning, and generative AI.
• Partner with business and technology leaders to translate strategic priorities into scalable technical solutions.
• Support data domains including marketing, merchandising, planning, supply chain, order fulfillment, consumer sales, retail, finance, and product development.
• Improve data quality, observability, lineage, security, governance, performance, and platform reliability.
• Optimize Snowflake and Databricks workloads for scalability, performance, maintainability, and cost efficiency.
• Define and promote engineering best practices, including version control, automated testing, CI/CD, code reviews, documentation, and infrastructure automation.
• Lead technical design and architecture reviews, evaluating tradeoffs across platforms, technologies, and implementation approaches.
• Diagnose and resolve complex issues affecting pipelines, data platforms, integrations, and downstream applications.
• Mentor data engineers and provide technical guidance across internal and distributed delivery teams.
• Collaborate with data science and AI teams to ensure enterprise data is accessible, governed, and production-ready for advanced use cases.

Required Qualifications

• 5+ years of experience in data engineering, software engineering, data architecture, or a related discipline.
• Experience operating as a principal engineer, technical lead, data architect, or senior engineering leader.
• Advanced hands-on experience with Microsoft Azure, Snowflake, Azure Data Factory, and Azure Databricks.
• Strong programming experience with Python and PySpark.
• Expert-level SQL skills, including query optimization and performance tuning.
• Demonstrated experience designing and delivering enterprise-scale ETL and ELT pipelines.
• Strong knowledge of dimensional modeling, normalized modeling, medallion architecture, lakehouse patterns, and semantic data structures.
• Experience integrating data from enterprise platforms, cloud applications, REST APIs, and third-party sources.
• Experience implementing data quality, metadata management, lineage, governance, privacy, and access-control standards.
• Strong understanding of Git-based development, automated testing, CI/CD, and modern software-engineering practices.
• Experience designing data platforms that support business intelligence, self-service analytics, data science, and AI workloads.
• Demonstrated ability to establish technical standards and influence engineering teams across organizational boundaries.
• Strong communication skills with the ability to explain technical decisions and tradeoffs to both technical and business audiences.

Preferred Qualifications

• Experience in retail, apparel, consumer products, e-commerce, or another customer-focused industry.
• Experience integrating data from ERP, CRM, customer data platforms, digital commerce, marketing, planning, order-management, or supply-chain systems.
• Familiarity with Power BI, Microsoft Fabric, MicroStrategy, Tableau, or comparable analytics platforms.
• Experience with event-driven architecture, streaming data, microservices, or serverless technologies.
• Familiarity with data mesh, domain-oriented data products, and federated governance.
• Experience supporting machine learning, generative AI, large language models, embeddings, or vector-based applications.
• Familiarity with MLOps, feature engineering, model deployment, and production AI monitoring.
• Experience modernizing legacy data ecosystems and migrating workloads to Azure, Snowflake, or Databricks.
• Experience collaborating with offshore or geographically distributed engineering teams.

What Success Looks Like

• A scalable and clearly defined architecture for the enterprise data platform.
• Reliable, observable, and reusable data pipelines across critical business domains.
• Improved engineering consistency through common standards and reusable development patterns.
• Higher-quality, more accessible data for analytics, reporting, data science, and AI.
• Faster delivery of new data capabilities without compromising governance, security, or maintainability.
• Strong alignment across engineering, architecture, analytics, data science, and business teams.
• Meaningful mentorship and technical development of the broader data-engineering organization.

About BICP

BICP is an AI, analytics, and engineering consultancy that helps organizations turn complex data and technology investments into measurable business outcomes. We provide specialized expertise and experienced delivery teams across modern data foundations, advanced analytics, artificial intelligence, and enterprise transformation.

This position offers the opportunity to help shape a modern data ecosystem within a rapidly growing consumer organization and deliver capabilities that directly support its customers, products, operations, and continued growth.