Job Opportunities API

At Adsquare, our mission is driven by our core focus:  Passion –  Solving complex challenges with great people, tech, and data.  Niche – Location Intelligence for Programmatic Advertisers.  Our core values are integral to everything we do: Drive: We turn ambition into action. Resilience:  We adapt, persevere, and grow stronger. No BS:  We value honesty, transparency, and clear communication. Humble:  We choose modesty over vanity and let results speak for themselves. Moral Compass:  We do the right thing with fairness, integrity, and respect. We seek candidates who not only bring excellent technical expertise but also embody these values in every aspect of their work. Scientific Problem Solving & Deep Dives: Act as an investigative engineer. Formulate hypotheses and dive deep into data, logs, and telemetry to understand analysis results, explain unexpected anomalies, and gather evidence. You won't just move data; you will scrutinize it to understand what is being processed (e.g., identifying when we are processing useless data that drives up costs). Pipeline Engineering: Build, deploy, and maintain robust transformation pipelines for high-volume data spanning the full lifecycle: ingestion, transformation, testing, deployment, and monitoring. Optimization & SQL Mastery: Write highly efficient code and relentlessly optimize SQL queries. You will analyze query execution plans, refactor legacy systems, eliminate redundancies, and improve pipeline efficiency to reduce cloud compute costs (e.g., optimizing Athena/Snowflake/Redshift clustering or AWS Glue jobs). AI-Augmented Engineering: Responsibly and intelligently leverage agentic AI tools (CLI or IDE-based) as core instruments in your daily workflow for more efficient planning, architecting, and implementation of features. Data Quality & Observability: Focus on infrastructure monitoring and telemetry rather than just business dashboards. Implement robust alerts and checks (e.g., dbt tests, Great Expectations) to catch data quality issues at the source. Software Engineering Best Practices: Adhere to and promote technical rigor using CI/CD workflows, containerization (Docker), and automated testing. Collaborate with Senior Engineers on architecture and code reviews. We are looking for a Data Analytics Engineer who approaches data with a software engineering mindset. You will join our Data Solutions squad to build and maintain production-grade data platforms . This is not a Data Analyst role. While you will understand the business context, your primary focus is technical: building scalable workflows, writing clean and testable Python/SQL code, automating deployments, and supporting cloud infrastructure optimizations. You will ensure our pipelines remain reliable, cost-effective, and maintainable. We are looking for a candidate who has solid analytics engineering experience or a strong background in backend development focused on data. We are looking for a Data Analytics Engineer who approaches data with a software engineering mindset but thinks like a scientist. You will join our Data Solutions squad to build and maintain production-grade data platforms. We are seeking proactive, inquisitive problem solvers who look well beyond the surface of a task. We want engineers who ask "why?", formulate hypotheses, and closely examine the data itself to understand underlying pipeline behaviors. You know that a pipeline's efficiency is directly tied to the nature of the data flowing through it, and you gather empirical evidence to guide your architectural decisions. While you understand the business context, your primary focus is technical and analytical: building scalable workflows, diagnosing complex data issues through evidence gathering, writing exceptional Python/SQL code, and optimizing cloud infrastructure. Must-Have Skills Rigorous Educational Background:  At least a B.Sc. (M.Sc. or Ph.D