• Build and maintain data pipelines for ingestion, transformation, and reporting with guidance from senior team members • Support Data Science and Business Intelligence teams with data preparation and quality assurance • Help monitor and troubleshoot data pipeline issues under supervision • Contribute to improving data quality and pipeline reliability initiatives • Learn to work with distributed systems and cloud technologies • Write clean, well-documented code following established team practices • Develop well-documented, tested data pipelines following team coding standards and best practices • Participate in code reviews and collaborative design sessions to continuously improve your technical skills • Work closely with product stakeholders to understand business requirements and translate them into technical solutions • Support data quality monitoring and help identify and resolve data issues • Contribute to team documentation and knowledge sharing initiatives • Stay curious and continuously learn new technologies and techniques

• Develop and optimize data pipelines • Build and maintain analytical, high-performance, and well-documented data models in BigQuery • Implement and manage monitoring and testing frameworks to ensure data quality and integrity • Lead the definition and enforcement of data governance policies, including organization and cataloging of data assets • Serve as a technical reference, promoting best practices in data engineering and data modeling across the team • Collaborate with business stakeholders to understand requirements and ensure data is accessible and documented

• Develop end-to-end ELT pipelines that integrate data from multiple sources to power a reliable and scalable data platform • Design and build high-performance, reusable data models that efficiently handle large datasets and support analytics, marketing, and machine learning use cases • Create and maintain APIs that enable seamless data sharing across systems, including APIs for deploying and serving machine learning models in production • Partner with engineering, data, and business teams to drive and deliver impactful data engineering initiatives • Contribute meaningfully to the design and implementation of core data infrastructure decisions

• As a Principal Data Architecture Consultant, you act as a senior technical leader in complex data and analytics engagements. • You shape and govern end-to-end enterprise data architectures, lead technical teams, and serve as a trusted technical advisor for clients and internal stakeholders. • You are responsible for ensuring that enterprise data and analytics solutions are scalable, secure, and production-ready, while translating business requirements into robust technical designs and delivery roadmaps. • Define and govern target enterprise data, integration and analytics architectures across cloud and hybrid environments • Translate business objectives into scalable, secure, and compliant data solutions • Lead the design of end-to-end data solutions (ingestion, integration, storage, security, processing, analytics, AI enablement) • Guide delivery teams through implementation, rollout, and production readiness • Function as senior technical counterpart for client architects, IT leads, and engineering teams • Mentor data architects, system architects and engineers and contribute to best practices and reference architectures • Support pre-sales and solution design activities from a technical perspective