Staff/Senior Data Engineer

Accountabilities:: Design, implement, and scale the organization's data warehouse and analytics infrastructure, creating a reliable foundation for enterprise-wide data consumption. Build and maintain data ingestion pipelines that integrate information from PostgreSQL, Google Cloud Storage, Jira, web analytics platforms, and other sources into BigQuery. Develop and manage data transformation workflows using dbt, converting raw datasets into structured, user-friendly data marts that support AI, business intelligence, and analytics applications. Define and implement scalable data exchange strategies, enabling reliable inbound data feeds, including product catalogs and planograms, as well as large-scale outbound data deliveries and cloud-native data sharing with clients. Establish infrastructure and processes that ensure external data transfers are scalable, secure, traceable, and efficient. Monitor cloud infrastructure and data warehouse spending, implementing cost controls and optimization strategies to maintain predictable operating expenses. Collaborate with application database teams to improve cloud architecture, leverage infrastructure synergies, accelerate access to insights, and reduce overall cloud costs. Establish comprehensive data quality frameworks using dbt testing capabilities, ensuring the accuracy, consistency, and reliability of analytical datasets. Develop and maintain standardized metric definitions, data documentation, and governance practices that make trusted data accessible across the organization. Champion DataOps principles and empower analytics engineers and data scientists to independently develop and manage reliable metrics and analytical workflows. Implement and maintain appropriate access controls and permissions across data consumption environments. Ensure data infrastructure complies with GDPR, personally identifiable information (PII) requirements, SOC 2, and other relevant security and regulatory standards. Requirements: At least 5 years of hands-on experience working with SQL, BigQuery, Terraform, Apache Beam, Airflow, and Google Cloud Platform (GCP). Demonstrated experience designing, implementing, and managing end-to-end data warehouse solutions. Strong expertise in data modeling and developing analytical data architectures that support business intelligence and advanced analytics use cases. Practical experience with dbt and event-driven analytics is highly desirable. Strong proficiency in SQL and Python, with the ability to develop and maintain scalable data pipelines and transformation processes. Solid understanding of cloud infrastructure architecture, including the strengths, limitations, and use cases of transactional versus analytical databases. Experience implementing DataOps best practices and enabling cross-functional teams to independently build, maintain, and use analytical assets. Strong knowledge of data governance, security frameworks, access management, and regulatory compliance requirements. Bachelor's or master's degree in Computer Science or a related technical field is preferred, although equivalent professional experience may be considered. Excellent communication skills, with the ability to explain complex technical concepts clearly to technical and non-technical stakeholders. Strong sense of ownership, accountability, and autonomy, with the ability to independently manage priorities and deliver results. Proven ability to influence technical practices, promote best practices, and encourage consistent adoption of data standards across teams. Collaborative mindset and enthusiasm for working in a fast-paced, innovative environment focused on AI, robotics, and data-driven solutions. Benefits: Competitive annual base salary ranging from $135,000 to $170,000 , depending on experience, skills, and location. Potential additional equity compensation, providing employees with an opportunity to share in the organization's long-term growth. Comprehensive medical, financial, and other employee benefits. Total rewards package combining base salary, equity, incentives, and well-being support. Opportunity to work remotely within the United States. Exposure to cutting-edge artificial intelligence, robotics, and retail technology. Opportunity to shape data architecture and influence engineering best practices across a growing organization. Collaborative, inclusive, and innovative working environment that encourages continuous learning, transparency, and professional development. Opportunity to contribute to technology solutions that improve retail operations and deliver measurable value to customers worldwide.