Data Engineer

Get AI-powered advice on this job and more exclusive features. ESB Advertising is revolutionizing marketing analytics with Mackdata (www.mackdata.ai), our AI-powered business intelligence platform that serves multiple enterprise clients. Our sophisticated conversational AI system transforms how businesses interact with their advertising data by providing intelligent insights through natural language conversations. We're looking for a Data Engineer to expand our platform's reach by onboarding new clients and maintaining our growing multi-tenant data infrastructure. Role Overview As a Data Engineer on our Multi-Client AI Platform team, you'll be responsible for expanding Mackdata's reach by onboarding new enterprise clients and maintaining our data infrastructure that powers AI-driven insights. You'll work directly with client data sources, design custom database schemas, create data warehouse queries, and configure the knowledge files that enable our AI assistants to understand each client's unique business context. This role is essential to scaling our platform from individual clients to a comprehensive multi-tenant AI analytics solution. Key Responsibilities Client Onboarding & Data Integration Lead end-to-end client onboarding process for new enterprise accounts Connect and integrate diverse raw data sources (CRM systems, advertising platforms, POS systems, analytics tools) Design and implement client-specific ETL/ELT pipelines to transform raw data into standardized formats Work directly with client technical teams to establish secure data connections and API integrations Database Design & Query Development Create custom GCP data warehouse schemas and table structures tailored to each client's business model Write complex SQL queries to transform, aggregate, and prepare data for AI consumption Design efficient data models that support both historical analysis and real-time insights Optimize query performance and manage data costs across multiple client datasets AI Configuration & Knowledge Management Develop client-specific configuration files and data schemas Write detailed assistant instructions that help AI understand each client's business context and terminology Create and maintain knowledge files that define metrics, KPIs, and business rules for each client Collaborate with AI engineers to ensure data feeds properly into conversational AI assistants Platform Scaling & Maintenance Maintain and enhance our multi-tenant data infrastructure supporting multiple concurrent clients Monitor data quality, implement validation checks, and troubleshoot pipeline issues Ensure data security, compliance, and proper access controls across client boundaries Document data lineage and maintain comprehensive technical documentation for each client setup Technical Requirements Required Qualifications (must-have) Bachelors degree in Data Engineering, Computer Science, Information Systems, or a related field 3+ years of hands-on data engineering experience working with complex, multi-source data integrations Expert-level SQL skills with proven experience in BigQuery or other GCP-managed warehouses, including data modeling and query optimization Strong Python programming skills for building and automating data pipelines Experience with ETL/ELT frameworks (Apache Airflow, dbt, or similar) Hands-on integration of marketing and advertising data sources (Google Ads, Meta/Facebook, Salesforce, etc.) Experience with API integrations, data quality validation, and error handling Solid understanding of data warehousing concepts, dimensional modeling, and analytics best practices Knowledge of data security and privacy compliance requirements (GDPR, CCPA), including multi-tenant architectures Preferred Qualifications (nice to have) Broader experience with Google Cloud Platform services beyond warehouses (e.g., BigQuery ML, LookML) Domain expertise in marketing analytics, adtech platforms, or retail/e-commerce data strategy Familiarity with AI/ML workflows, including data preparation, feature engineering, and supporting LLM/conversational AI use cases Exposure to real-time data streaming and event-driven architectures Knowledge of data cataloging and metadata management tools Experience leading client-facing technical implementations and managing stakeholder relationships What You'll Work With Data Sources & Integrations Advertising Platforms: Google Ads, Facebook/Meta, Microsoft Advertising, Amazon DSP Analytics Tools: Google Analytics, Adobe Analytics, customer attribution platforms Data Warehouses: Google Cloud Platform (BigQuery), with potential client-specific sources Configuration Files You'll Create Business Logic: Metric calculations, KPI definitions, aggregation rules AI Instructions: Business context, response guidelines, domain expertise Category Mappings: Product taxonomies, channel classifications, geographic mappings What We Offer Competitive salary and comprehensive benefits package A collaborative, forward-thinking team environment with data scientists, AI engineers, and client success teams Direct impact on the evolution of Mackdata and ESB's AI-driven data future Opportunities for growth and innovation in the marketing technology space Direct ownership of client relationships and technical implementations Exposure to diverse industries and business models through our varied client base Ready to help build the future of AI-powered business intelligence? Join our team and play a crucial role in scaling cutting-edge technology that's transforming how businesses understand and interact with their data. Seniority level

Seniority level

Mid-Senior level Employment type

Employment type

Full-time Job function

Job function

Information Technology Industries

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