Software Engineer - Data & Full Stack (f/m/x)

Job description

What are the main performance objectives in this role? This role sits inside our 5-person Engineering team, running the high-volume data platform behind our mobile OEM advertising business: nightly ETL pipelines pulling from 10+ mobile attribution and ad-network partners (AppsFlyer, Adjust, Everflow, Kochava, Huawei, Xiaomi, Oppo, Vivo, Mintegral), an Amazon Redshift warehouse feeding BI, and our internal full-stack platform (APH) used daily by our media buyers and partner managers. As our Software Engineer, you'll work across data pipelines, the warehouse, and the internal product, with real ownership from day one. Concretely, that means: Building and maintaining Python ETL pipelines orchestrated on Apache Airflow (Amazon MWAA), running on ECS Fargate: API ingestion, S3 staging, Redshift COPY loads Developing and evolving our Redshift star-schema warehouse: fact/dimension modeling, SQL transformation jobs, Flyway schema migrations, query performance tuning (DISTKEY/SORTKEY), data quality and reconciliation checks Contributing full stack to our internal platform: Spring Boot 3 / Java 21 backend (WebFlux, R2DBC/PostgreSQL, Redshift analytics reads) and Vue.js frontend (Nuxt, Vuetify) Adding integrations with new ad-network and attribution partners end to end: API client → transformer → S3 → Redshift → reporting Owning reliability: idempotent re-runnable jobs, structured logging, monitoring/alerting, runbooks, and a light on-call rotation Reviewing teammates' PRs and writing reviewable, well-tested changes yourself What are the strengths, transferable skills, and behaviors that drive success in this role? Must haves (these are non-negotiable for day one): 3–5 years professional software engineering experience with production code in at least two of: Python, Java, SQL-heavy data work — and genuine willingness to work in all three Strong SQL — comfortable with window functions, CTEs, large joins; experience with a columnar/MPP warehouse (Redshift, Snowflake, BigQuery) or deep PostgreSQL experience and the curiosity to learn Redshift's differences Python for data pipelines — API clients, pagination/rate-limit handling, pandas or plain transforms, pytest AWS fundamentals — S3, IAM basics, and at least one of ECS/Lambda/EC2 in production Experience with batch/scheduled data workflows (Airflow preferred; Dagster/Prefect/cron-based acceptable) and an instinct for idempotency and failure handling Can read and modify a Java or similar typed backend codebase (Spring Boot a plus; C#/Kotlin backgrounds transfer fine) Nice-to-haves (valuable, but not required): Amazon MWAA specifically, or self-managed Airflow at scale Redshift specifics: COPY/UNLOAD, DISTKEY/SORTKEY design, WLM, stl_/svl_ system tables Spring WebFlux / reactive Java, R2DBC Vue.js/Nuxt experience (React experience transfers) Terraform/Terragrunt, Docker, GitHub Actions dbt or similar transformation frameworks Ad-tech / mobile attribution domain: MMPs (AppsFlyer, Adjust, Kochava), affiliate platforms (Everflow), postbacks, attribution windows, cost/revenue reconciliation Flyway or comparable migration tooling Two notes before you apply: We know that individuals who identify as women, trans, or non-binary tend to hesitate to apply for a role unless they meet almost all the requirements. If that resonates with you, we want to be clear: we're more interested in your potential than your ability to tick every box. Apply anyway. On compensation: At AVOW, pay is structured around a clear grade and level framework, with decisions based on objective criteria: your experience, qualifications, scope of responsibility, and role-specific requirements. We're transparent about how we make these decisions and will be discussing the details from our very first engagement. What does our hiring process look like? Intro call: A casual conversation with our TA team. We'll tell you about the role and the team; you tell us about yourself. Deep dive: A transparent conversation with your future hiring manager about the role, what success looks like, and where the team is headed. Problem-solving & pairing: A technical assessment of your skills. Meet the team: An informal coffee chat with a potential future colleague. What do we offer? Learning & Development opportunities Sabbatical policy Subsidies for public transportation, sports, and German courses Bike leasing program Healthy (also not so healthy) snacks in the office every day Experienced, innovative, diverse team Health insurance coverage for you and your family We are looking forward to getting your application!