Data Engineer; Backend Data, Marketing & AI

Data Engineer for Backend Data & AI (Digital & Marketing IT)

Location:
Alameda, CA Onsite / Hybrid

Full-time role

• 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
  .
• Design, develop, and optimize of ETL/ELT pipelines using a mix of AWS Glue, S3, Redshift, DynamoDB, external tables, App Flow, Five Tran, 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.
• 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.