• Implement and manage robust, scalable ETL/ELT pipelines to ingest, transform, and load data from Google Ads, Meta Ads, and Microsoft/Bing Ads APIs — as well as CRM, call tracking, and lead event sources — into our BigQuery data ecosystem • Own Bronze layer ingestion with full fidelity, audit trails, and zero silent failures • Build and maintain the permanent Cloud Run connector for the Microsoft Ads Reporting API (SOAP/OAuth2), replacing interim Dataslayer bridges as the platform matures • Integrate Pub/Sub-based event streaming for real-time lead data flows and speed-to-lead use case • Translate designs and specifications from the Data Architect into functional, production-grade data infrastructure and code • Extend the Medallion Architecture (Bronze → Silver → Gold), owning Silver layer transformation logic and Gold layer Dataform models serving Command Centre, client reporting, and future AI/ML consumers • Own the CDMID join logic that unifies CRM, ad platform, and call tracking data into a coherent lead record across all client accounts • Develop and manage data models within BigQuery, ensuring data is organized efficiently for analytics and AI/ML workloads • Apply dimensional modeling and star schema design principles to build a single source of truth for all reporting and analytics across our home improvement advertiser base • Deliver the clean, trusted, cost-metric-driven datasets that allow our team to move beyond vanity metrics to cost-per-issued-lead and cost-per-demo insights that drive real client decisions • Write Python-based automation scripts and leverage GCP services — Cloud Run, Cloud Functions, Pub/Sub, and Dataflow — to orchestrate data workflows and eliminate manual processes • Graduate CRM push workflows off Zapier and onto a reliable, auditable Cloud Run pipeline • Proactively monitor and tune data pipelines and BigQuery queries for performance and cost-efficiency • Implement data quality checks, validation rules, and monitoring across the full pipeline to ensure accuracy, completeness, and timeliness of all data assets • Build the observability and alerting layer so the team knows about data issues before clients do • Maintain living architecture documentation as a reliable source of truth across workstreams

• Own and manage the data pipeline for updating and adding records to our internal database of contact and company information • Complete data analysis requests for the engineering and product team • Evaluate and configure new data services • Own the overall improvement of our internal database of contacts and company records

• Design scalable data processing pipelines for streaming and batch processing using Big Data technologies like Databricks, Airflow and/or Dagster. • Contribute to the development of CI/CD and MLOps processes. • Develop applications to aggregate, process, and analyze data from diverse sources. • Collaborate with the Data Science team on Machine Learning projects, including text/image analysis and predictive model building. • Develop and organize data transformations using Databricks/DBT and Apache Airflow. • Translate business requirements into technical solutions and ensure optimal performance and quality.

• Develop and maintain a high-performance data processing platform for automotive data, ensuring scalability and reliability. • Design and implement data pipelines that process large volumes of data in both streaming and batch modes. • Optimize data workflows to ensure efficient data ingestion, processing, and storage using technologies such as Spark, Cloudera, and Airflow. • Work with data lake technologies (e.g., Iceberg) to manage structured and unstructured data efficiently. • Collaborate with cross-functional teams to understand data requirements and ensure seamless integration of data sources. • Monitor and troubleshoot the platform, ensuring high availability, performance, and accuracy of data processing. • Leverage cloud services (AWS) for infrastructure management and scaling of processing workloads. • Write and maintain high-quality Python (or Java/Scala) code for data processing tasks and automation.