Key Responsibilities
Technical Acumen & Architecture
Design with authority for backend data and AI solutions supporting Digital Marketing platforms.
Define and evolve modern data architecture standards, including Data Mesh, Medallion Architecture, Data Lake, and Lakehouse patterns.
Lead architecture and design reviews, ensuring solutions are scalable, secure and aligned with enterprise standards.
Translate business and marketing needs into clear technical designs, data models, and implementation patterns.
Data Engineering & Platform Delivery
Design, develop, and optimize of ETL/ELT pipelines using a mix of AWS Glue, S3, Redshift, DynamoDB, external tables, AppFlow, FiveTran, and Airflow.
Architect and implement customer data unification across CRM, marketing automation platforms, and third ‐ party data providers.
Own and optimize analytics-ready data warehouses and semantic layers on Amazon Redshift.
Define and maintain enterprise-grade data models, ER diagrams, and transformation logic to support downstream analytics and activation.
DBT, SQL & Python Excellence
Own DBT standards and best practices, including models, snapshots, tests, macros, and Jinja-based SQL templating.
Provide expert-level SQL guidance, including complex joins, window functions, and performance tuning.
Develop and review reusable Python frameworks and components for ingestion, transformation, orchestration, and automation.
AI & Advanced Analytics Enablement
Enable backend data structures and pipelines required for AI/ML and GenAI use cases, including feature-ready datasets and model inputs.
Partner with product analysts and analytics teams to support segmentation, personalization, predictive analytics, and attribution models.
Support data foundations for multi-touch attribution, ROI measurement, and AI-driven marketing insights.
Support the building and management of BI dashboards in partnership with offshore BI Engineers.
Team Enablement
Provide technical leadership and support to onshore and offshore engineers; perform design and code reviews.
Contribute to the team 's on CI/CD best practices, version control (Git), and automated testing for data pipelines.
Act as a key escalation point for complex data issues, performance challenges, and production incidents.
Collaborate with product managers, architects, compliance, and business stakeholders to ensure successful delivery.
Establish and enforce data quality, validation, and observability standards across data products.
Data Engineer for Backend Data & AI (Digital & Marketing IT)
Location: Alameda, CA Onsite / Hybrid
Long-Term Rolling Contract
Role Summary
We are seeking a hungry to learn and grow Data Engineer for Backend Data & AI with 5+ years of hands-on data engineering experience and a proven ability to lead architecture, execution, and technical direction for enterprise-scale marketing and customer data platforms. This role will act as a technical authority and thought leader, guiding backend data and AI solutions that power customer engagement, marketing activation, analytics, and AI-driven insights.
The ideal candidate combines strong technical expertise in AWS, DBT, Python, and modern data architectures with good leadership, communication, and decision-making skills . You will partner closely with product owners, marketing stakeholders, technical leads, architects, and offshore delivery teams to deliver scalable, business-ready data solutions.
Required Qualifications
Nice to Have