Lead Data Engineering and Analytics team to oversee data infrastructure design and governance for robotic deliveries. Collaborate cross-functionally to enable data-driven decision-making across departments.
Responsibilities
Lead, mentor, and grow a team of data and analytics engineers. This includes hiring, performance management, career development, planning, and setting technical standards.
Define the data engineering and analytics roadmap, aligned with company goals. This includes prioritizing data platform investments, reporting needs, analytics capabilities, and cross-functional data initiatives.
Oversee the design, reliability, scalability, and governance of the company’s data infrastructure, such as data warehouses, data lakes, ETL/ELT pipelines, orchestration systems, semantic layers, and BI tooling.
Ensure business stakeholders have accurate dashboards, metrics, reporting, and ad hoc analysis to support decision-making across functions such as product, operations, finance, sales, marketing, and executive leadership.
Make self-service an organization-wide goal by building rich, trusted datasets and enabling access through AI-powered natural language interfaces.
Establish standards for data accuracy, lineage, documentation, access controls, privacy, security, and compliance.
Requirements
6+ years of professional experience in data engineering and analytics including 2+ years experience leading teams of Sr. Data/Analytics Engineers.
Proven experience managing data engineering, analytics engineering, BI, or analytics teams, including hiring, coaching, performance management, and roadmap planning.
Deep understanding of data warehouses, data lakes, ETL/ELT pipelines, orchestration, data modeling, BI platforms, semantic layers, and data quality practices.
Hands-on experience with tools such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Fivetran, Looker, Tableau, Power BI, or similar platforms.
Strong track record partnering with executives and teams across product, operations, finance, engineering, sales and marketing, translating business goals into data strategy, dashboards and analytics products that improve decision-making.
Demonstrated ability to build trusted, governed data products and enable organization-wide access through natural language or AI-powered analytics interfaces, with strong controls for accuracy, security, privacy, compliance and usability.
Experience establishing standards for data quality, documentation, access controls, privacy, security, auditability, metric definitions, and trusted data products, including SOX, SOC2 compliance and compliance with international data policies and regulations (e.g., GDPR, data residency requirements).
Bachelor’s degree in computer science, data science, engineering, statistics, mathematics, information systems, or a related field. Advanced degrees are a plus.
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