I.T. Solutions, Inc.

Tech Lead – Backend Data & AI (Digital & Marketing IT)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Tech Lead – Backend Data & AI with 8+ years of data engineering experience, focusing on AWS, DBT, Python, and modern data architectures. It's a long-term onsite contract in Alameda, CA, requiring strong leadership and communication skills.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
600
-
🗓️ - Date
April 25, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Alameda, CA
-
🧠 - Skills detailed
#Data Architecture #Data Enrichment #Automation #Scala #ML (Machine Learning) #Data Quality #Macros #Airflow #Data Lake #GIT #Amazon Redshift #DynamoDB #Observability #Data Warehouse #Data Engineering #Compliance #Python #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Leadership #Alation #CRM (Customer Relationship Management) #Version Control #GDPR (General Data Protection Regulation) #SQL (Structured Query Language) #dbt (data build tool) #Code Reviews #Redshift #Automated Testing #Cloud #Data Pipeline #BI (Business Intelligence) #Fivetran #S3 (Amazon Simple Storage Service) #"ETL (Extract #Transform #Load)" #Datasets #AWS Glue
Role description
Title: Tech Lead – Backend Data & AI (Digital & Marketing IT) Location: Alameda, CA (Onsite) Long-Term Rolling Contract Role Summary • We are seeking an experienced Tech Lead – Backend Data & AI with 8+ 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 deep technical expertise in AWS, DBT, Python, and modern data architectures with strong leadership, communication, and decision-making skills. You will partner closely with product owners, marketing stakeholders, architects, and offshore delivery teams to deliver scalable, secure, and business-ready data solutions. Required Qualifications: • 8+ 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. Key Responsibilities Technical Leadership & Architecture • Serve as Tech Lead and design authority for backend data and AI solutions supporting Digital and 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, cost-effective, and aligned with enterprise standards. • Translate business and marketing needs into clear technical designs, data models, and implementation patterns. Data Engineering & Platform Delivery • Lead the design, development, and optimization of ETL/ELT pipelines using 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. Data Quality, Governance & Compliance • Establish and enforce data quality, validation, and observability standards across data products. • Ensure data solutions meet governance, privacy, and compliance requirements, particularly for marketing and customer data. • Drive consistency in business definitions, metrics, and golden data assets. • Marketing Data Enablement Focus Build and optimize data flows that support campaign targeting, segmentation, and personalization across email, paid media, and social channels. • Implement marketing-specific data enrichment and validation logic (e.g., opt-in status, best email logic, engagement scoring). • Enable analytics and dashboards for campaign performance, attribution, and customer journey insights. 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. Delivery Oversight & Team Enablement • Provide technical leadership and mentorship to onshore and offshore engineers; perform design and code reviews. • Guide teams 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. 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. • 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.