Job Opportunities API

About GrowthLoop GrowthLoop is a pioneer in AI-powered marketing on the data cloud, featured on G2 by its customers as a momentum leader with the best ROI for enterprise. Founded and led by former Google executives, GrowthLoop helps innovative companies transform how they market and drive business impact. The GrowthLoop Compound Marketing Engine drives compound growth by accelerating the marketing cycle, using Agentic AI powered by your enterprise cloud data. Growth Agents propose audiences and journeys, and activate campaigns across channels, streamlining execution and continuously analyzing performance data to make suggestions for campaign optimization.   Thousands of marketers at enterprises like Google, Costco, and Albertsons rely on GrowthLoop to grow faster with agentic AI, drive measurable campaign results, and maximize marketing ROI—compounding growth with every experiment, iteration, and campaign. How We Work  Love Our Customer - We win when our customer wins. Make It So - We turn decisions into outcomes. Put We Over Me - We succeed together—or not at all. Be Human - Goodness and kindness compounds. Aim High - We’re here for the long game—act like it. The Opportunity In this role, you will be embedded with a single enterprise client, acting as a key technical partner in their data transformation journey. You'll gain deep knowledge of their business by collaborating closely to design efficient, accessible data models that unlock real business value. This role offers the unique opportunity to make a significant impact on a high-priority, strategic initiative. You're passionate about clean data architecture, skilled at breaking down complex problems into manageable parts, and you appreciate the long-term value of scalable tooling and repeatable processes. If you thrive in a fast-paced environment with autonomy, growth potential, and purpose-driven work, this role is for you. What You’ll Do Engineer and optimize the ingestion of large volumes of data into cloud data warehouses Work directly with a single enterprise client to understand their business needs, data landscape, and roadblocks Design and build scalable data models that support the client's analytical and operational goals Drive improvements to internal workflows and tooling to increase efficiency and repeatability Serve as a thought partner for client stakeholders, guiding technical and strategic data decisions What We Look For Core Requirements 2–5 years of experience as a Data Engineer or Analytics Engineer, with strong proficiency in SQL and Python Proven experience designing, building, and maintaining cloud data warehouses (e.g., BigQuery, Snowflake, Redshift) Hands-on experience with Google Cloud Platform (GCP), including core services such as BigQuery Strong data modeling skills, with the ability to design scalable, well-structured models for both analytical and operational use cases Experience working with BI and visualization tools (e.g., Looker, Tableau, Power BI, or similar) Solid understanding of relational databases and core data warehousing principles Strong analytical thinking and problem-solving abilities Self-starter who thrives in autonomous environments and takes ownership of outcomes Naturally curious, with a passion for learning and applying new tools and technologies Bonus Points If You Have  Experience with transformation and modeling tools such as dbt or Google Cloud Dataform Experience with workflow orchestration platforms like Airflow Exposure to machine learning workflows, including model development, training, deployment, or productionization Experience working with or within large enterprise organizations We are a collaborative, growth-minded team that believes in taking the learner's mindset into everything we do. This role offers the opportunity to expand into machine learning and AI, applying modern