Analytics Engineer

INTRO 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. YOUR MISSION * 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. YOUR PROFILE 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. WHAT YOU WILL DO 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. strongly preferred) in Computer Science, Mathematics, Physics, Neuroscience, Economics, or another empirical science field that emphasizes the scientific method and evidence-based problem solving. * Experience: 2+ years of experience specifically in Analytics Engineering, Data Engineering, or backend development heavily focused on data. * Scientific & Analytical Mindset: Proven ability to work hypothesis-driven, dissecting logs, telemetry, and raw data to solve complex problems and explain unexpected pipeline behaviors. * Excellent Python Proficiency: You have deep experience developing and deploying production-grade Python code. You are highly skilled in both object-oriented and functional programming paradigms, write modular code, utilize advanced testing libraries, and deeply understand exception handling, logging, and system optimization. * Advanced SQL & dbt: Exceptional ability to build scalable data models (Jinja templating, macros, incremental strategies). You have a deep understanding of query execution plans and a track record of rigorous SQL query optimization. * Agentic AI Proficiency: Demonstrated ability to smartly and responsibly utilize agentic AI coding assistants to accelerate development and architecture—this is a core requirement, not a novelty. * Software Engineering Fundamentals: Hands-on experience with Git flows, CI/CD pipelines (e.g., GitHub Actions, GitLab CI), and Containerization (Docker). * AWS Cloud Native Experience: Experience building and maintaining data workflows using serverless architectures such as AWS Lambda, StepFunctions, Glue, and Athena. * Testing Mindset: Experience implementing Unit Tests and Integration Tests for data pipelines rather than relying solely on manual checks. * Data Warehouse Ops: Solid understanding of warehousing architecture (Snowflake, Redshift, or BigQuery), including partitioning and clustering concepts. NICE TO HAVE * Infrastructure as Code: Experience with Terraform to manage cloud resources. * Orchestration: Experience with modern data orchestration tools like Airflow, Dagster, or Prefect. * Big Data: Knowledge of big data processing frameworks (Spark/PySpark). * Dashboarding: Familiarity with visualization tools (Streamlit, Preset, Tableau, etc.) primarily used for debugging and system monitoring. WHY US? On top of a competitive package… * We are open to flexible work models: we work in a hybrid mode and remotely from anywhere in the world up to 3 months per year. * To encourage education and professional growth, we offer an individual yearly budget of 1.200€. * You are entitled to 30 vacation days per year. * We offer Urban Sports Club membership, company pension scheme. * Regular team events and company events organised by our People team (Trust us, they know how to throw a party!). * We equip you with the latest hardware and provide you with all the tools you need to thrive. SALARY RANGE (ANNUAL ON-TARGET EARNINGS) 60,000 - 75,000 euros RECRUITING PROCESS For technical roles (Data, Engineering, and Product), candidates are encouraged to upload any technical certifications referenced in their CV via the "Other Documents" section of the application form. Alternatively, certification documents may be submitted after the first technical interview. Any certifications listed on the CV must be provided and successfully validated before proceeding to the second technical interview stage. * Step 1: Online quizzes (45 mins). * Step 2: Value-based interview (30 mins). * Step 3: Deep-dive technical interview (1.5 hours) with the Data team. * Step 4: Practical data-crunching challenge. * Step 5: Team Meet & Greet — the final step to ensure we're a great fit for each other. WORK MODEL Hybrid DESIRED START DATE As soon as possible

INTRO 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 top-tier technical expertise but also embody these values in every aspect of their work. ABOUT THE TEAM We are looking for a Staff Data Analytics Engineer to join our technical proficiency track. This is a highly technical, Individual Contributor (IC) role. You will act as the Technical Lead for your squad—making critical architectural decisions, defining engineering standards, and driving cross-squad collaboration—without the responsibilities of people management. You will be the technical north star for the team, approaching extremely complex data problems with a rigorous software engineering mindset. You will design, build, and oversee production-grade data platforms that process massive volumes of geo-spatial data, audience attributes, and geo-location time-series data. YOUR PROFILE We are looking for an exceptional engineer who has a proven track record of acting as a technical leader and domain expert in heavy data environments. Must-Have Skills: * 7+ years of experience in Data Engineering, Analytics Engineering, or Backend Development with a deep focus on massive data systems. * Geo-Spatial & Time-Series Expertise: Proven, hands-on experience handling massive datasets specifically involving geo-spatial (GIS) data, audience attributes, and high-frequency time-series data. * Advanced Software Engineering (Python): Mastery of Python beyond standard data scripting. You write highly modular, object-oriented code. You have deep, practical experience with Test-Driven Development (TDD), mocking, exception handling, and performance profiling, functional programming. * Architectural Vision: Deep expertise in designing scalable data architectures using both relational and horizontally scalable data warehouses/lakehouses (e.g., Snowflake, Redshift, Athena, StarRocks, Iceberg). You deeply understand query execution plans, partitioning, clustering, and cloud cost governance. * Big Data Frameworks: Extensive experience with large-scale data processing frameworks (e.g., Apache Spark, PySpark, AWS EMR, Glue) to handle massive throughput. * Expert SQL & dbt: You design scalable, robust data models (using Jinja, macros, incremental strategies) that serve as the foundation for our entire analytics layer. * AWS Cloud Native & IaC: Hands-on experience building architectures in AWS (e.g.: AWS Lambda, AWS Batch, Glue, StepFunctions, S3, EC2, ECS, ECR, Fargate) and deploying them using Infrastructure as Code (Terraform). * Leadership Skills: Superb organizational and communication skills. You can distill complex architectural trade-offs for non-technical stakeholders and drive technical consensus among your engineering peers. Nice-to-Have Skills: * Polyglot Programming: Experience with a compiled or strongly typed language (e.g., Scala, Go, Kotlin, C++ or Java). * Advanced Orchestration: Experience defining complex dependency graphs in tools like Airflow, Dagster, or Prefect. WHAT YOU WILL DO * Technical Leadership & Architecture: Act as the principal architect for your squad. You will design horizontally scalable, cost-efficient, production-grade data solutions capable of handling TB-scale, highly dimensional datasets. * Engineering Excellence & TDD: Champion rigorous software engineering principles. You will lead the adoption of Test-Driven Development (TDD), CI/CD workflows, and clean code architectures. You ensure our codebase is resilient, testable, and maintainable. * Cross-Squad Impact: Drive technical alignment beyond your immediate team. You will act as an engineering ambassador, solving architectural issues that span multiple squads, keeping our technical processes synchronized, and aligning your squad's work with global engineering priorities. * Domain Mastery: Leverage your deep expertise to build high-value data products on top of location signals and audience attributes. You don't just process data; you deeply understand its geographic and time-series nature to unlock its business value. * Mentorship & Code Quality: Be the technical mentor for Senior, Mid, and Junior engineers. Through highly insightful code reviews, architectural feedback, and pair programming, your input will consistently be the source of others’ learning and growth. * Data Observability: Proactively build monitoring and alerting frameworks at the infrastructure level to catch anomalies in our multi-terabyte data streams before they impact downstream products. WHY US? On top of a competitive package… * We are open to flexible work models: we work on a hybrid mode and remotely  * To encourage education and professional growth, we offer an individual yearly budget of 1.200€ * You are entitled to 30 vacation days per year * We offer Urban Sports Club membership, company pension scheme * Regular team events and company events organised by our People team (Trust us, they know how to throw a party!) * We equip you with the latest hardware and provide you with all the tools you need to thrive SALARY RANGE (ANNUAL ON-TARGET EARNINGS) 90,000 - 100,000 euros RECRUITING PROCESS COULD REQUIRE ON SITE STEPS For technical roles (Data, Engineering, and Product), candidates are encouraged to upload any technical certifications referenced in their CV via the "Other Documents" section of the application form. Alternatively, certification documents may be submitted after the first technical interview. Any certifications listed on the CV must be provided and successfully validated before proceeding to the second technical interview stage. * Step 1: Short 30-min take-home technical quiz. * Step 2: Value-based interview (30 mins). * Step 3: Deep-dive technical interview (1.5 hours) with the Data team. * Step 4: Practical data-crunching challenge. * Step 5: Team Meet & Greet — the final step to ensure we’re a great fit for each other. WORK MODEL Hybrid DESIRED START DATE Asap