Role Description The Principal Data Architect will lead the design, modernization, and long-term strategy of our enterprise data ecosystem. This role is both strategic and hands-on — ideal for someone who can architect large-scale solutions while actively contributing to modeling, integrations and implementation. You will shape a modern data foundation supporting commerce, operations, customer experience, analytics, personalization, and executive decision enablement across the organization. Key Responsibilities - Define and own the enterprise data architecture roadmap, ensuring scalability, maintainability, and alignment with business strategy. - Design and implement sophisticated data models supporting commerce, customer lifecycle, finance, supply chain, inventory, and digital transformation initiatives. - Build and optimize secure data pipelines integrating Shopify and multiple enterprise systems into a unified Snowflake and SQL Server environment. - Lead standards for data governance, privacy, lineage, cataloging, quality, and master data management. - Drive best practices for Power BI semantic models, architecture, and performance governance across business functions. - Provide architectural oversight for ELT frameworks, automation, and orchestration tools (dbt, Airflow, Matillion, Fivetran, etc.). - Partner with engineering, data, product, and business teams to translate requirements into scalable, future-proof solutions. - Mentor internal data engineering teams and influence leadership on data strategy and platform investment decisions. - Serve as the senior technical authority for data architecture across the organization. Qualifications - 7–10+ years experience in enterprise data engineering, architecture, or platform ownership roles. - Proven expertise in: - Snowflake (design, security, cost management, workload optimization) - SQL Server (schema design, tuning, stored procedures, indexing) - Advanced SQL capability with demonstrated experience optimizing large, complex, high volume workloads. - Strong experience implementing and supporting Power BI enterprise deployments (governance, semantic layer design, modeling patterns). - Hands-on experience with modern ELT tooling and orchestration (dbt, Airflow, Fivetran, Stitch, Matillion, Databricks, etc.). - Demonstrated eCommerce data experience, ideally including Shopify — understanding of order lifecycle, OMS, payments, fulfillment, customer segmentation, and attribution. - Experience building scalable architecture frameworks aligned to business intelligence, operational reporting, and AI/ML readiness. Preferred Experience - Retail or multi-channel commerce experience (stores + eCommerce). - API experience (REST / GraphQL) and complex system integrations. - Knowledge of compliance and governance: SOC2, GDPR, CCPA, PCI-DSS. - Python experience for workflow automation or integration scripting. Preferred Characteristics - A senior technical leader who is both visionary and execution-minded. - Able to influence at executive level while guiding implementation details. - Practical and business-oriented — not just an architect on paper. - Thrives in transforming legacy data landscapes into modern, scalable platforms. Benefits - Full Time Opportunity – A comprehensive benefits package is available. - Rewarding Environment and Competitive Pay. - Generous Dream Maker Discount After First Pay Period. - Referral Incentive Program. - Dayforce Wallet – Get Paid Early! - Health/Dental/Vision Insurance. - 401K Program. - Paid Vacation, Wellness Days & Holidays, including your Birthday off! - Pet Benefits.

• Design and architect comprehensive data center infrastructure solutions, including network, storage, compute, and security components • Develop and communicate technical strategy and roadmap for data center projects, ensuring alignment with organizational objectives • Lead project planning, execution, and delivery, managing timelines, budgets, and resource allocation effectively • Oversee cross-functional teams including engineers, vendors, and stakeholders to ensure successful project outcomes • Conduct detailed technical assessments and feasibility studies to evaluate data center requirements and optimization opportunities • Ensure all data center designs comply with industry standards, regulatory requirements, and best practices • Mentor and guide technical teams, fostering a culture of continuous learning and technical excellence • Analyze and optimize data center performance, efficiency, and cost-effectiveness through innovative solutions • Evaluate emerging technologies and recommend adoption strategies for data center modernization • Manage vendor relationships and evaluate third-party solutions for data center infrastructure components

• Building state of the art pipelines and data models that are at the heart of the studio decision-making process. • Working on large-scale lakehouse and warehouse analytics systems that process data feeds in real-time and batch processes.

Role Description This is a full-time, high-impact position for a Senior Data Engineer with expertise in Databricks, dbt, and Apache Airflow to support a critical CRM data architecture migration for a key client in the Life Sciences industry. - Join an urgent initiative to backfill key engineering capabilities and maintain momentum during an ongoing CRM system transition. - Migrate enterprise customer data from Veeva CRM to Salesforce Life Sciences Cloud, integrated with an underlying AWS S3 cloud environment and Databricks data warehouse. - Build out, configure, and redirect data ingestion pipelines out of Life Sciences Cloud into the data warehouse. - Implement dbt models and Airflow orchestrations to ensure complete data accuracy. Candidates must be able to operate strictly on US East Coast business hours (location is flexible across North America, LATAM, or remote with full Eastern Time overlap). Qualifications - 5+ years of hands-on data engineering experience with deep expertise in AWS, Databricks, dbt, and Apache Airflow. - Strong programming proficiency in Python/PySpark and Advanced SQL (complex joins, analytical window functions). - Hands-on expertise in Databricks platform architecture, Lakehouse implementation, Delta Lake, Unity Catalog, and cluster performance tuning. - Proven track record of architecting and executing migrations. - Demonstrated experience scaling platform performance. - Proven experience building scalable transformations pipelines using dbt for data transformation, testing, and documentation. - Solid background orchestrating complex workflow DAGs with Apache Airflow. - Experience working with AWS cloud infrastructure, specifically AWS S3 as an underlying data lake storage layer. - Hands-on experience developing integrations and data ingestion pipelines for CRM platforms, specifically Salesforce, Salesforce Life Sciences Cloud, and/or Veeva CRM. - Understanding of data structures, customer master data, and analytics workflows within the Life Sciences. - Deep understanding of SDLC/Agile and DevOps for CI/CD and artifact management. - Knowledge of AWS and Databricks security best practices and compliance standards. - Certifications Preferred: Databricks Certified Data Engineer Associate/Professional, Databricks Spark Developer, and major cloud certifications in AWS. Requirements - Ability to maintain 100% full working time overlap with US East Coast business hours (ET). - Flexible location (US, Canada, LATAM, or remote ET). Responsibilities - Architect, build, and deploy data integration pipelines connecting Salesforce Life Sciences Cloud to the client’s Databricks warehouse environment. - Execute pipeline modifications to transition legacy data feeds from Veeva CRM to Salesforce Life Sciences Cloud, updating warehouse models accordingly. - Write clean, modular dbt transformation models and organize end-to-end DAG execution using Apache Airflow. - Manage Delta tables and optimize Databricks clusters and AWS S3 storage for high performance and cost efficiency. - Implement data quality testing, schemas, and verification rules in dbt and Python to guarantee accurate data delivery. - Build and enforce proactive monitoring frameworks. - Work closely with project leads, solution architects, and technical stakeholders during US East Coast hours to ensure rapid iteration and goal completion. Equal Opportunity Employer Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.