Data Engineer (Backend Data, Marketing & AI)

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 • 5 + years of experience in data engineering, with at least 2–3 years in a technical leadership or lead engineer role. • Deep expertise in AWS data services (Glue, S3, Redshift, DynamoDB, Airflow). • Advanced proficiency in SQL, DBT, and Python. • Strong experience designing and operating cloud-native data platforms at scale. • Proven ability to communicate complex technical concepts to both technical and non-technical stakeholders. Nice to Have • Experience in the Life Sciences or Healthcare domain. • Strong familiarity with marketing data ecosystems (email, media, social, web) and key Marketing KPIs. • Data flows that support campaign targeting, segmentation, and personalization across email, paid media, and social channels. • Marketing-specific data enrichment and validation logic (e.g., opt-in status, best email logic, engagement scoring). • Data engineering supporting analytics and dashboards for campaign performance, attribution, and customer journey insights. • Experience with Fivetran or similar managed ingestion tools. • Knowledge of marketing compliance and privacy regulations (GDPR, HIPAA for HCP data, CAN-SPAM). • Experience with CRM platforms such as Salesforce or Veeva. • Exposure to GenAI, LLMs, and AI-driven personalization frameworks. 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.