Data Engineer AA-09

About the Company Founded in 2013, our partner is a leader in performance-based mobile app marketing, partnering globally to deliver premium users at scale. Their collaborative team prioritizes innovation and strategic decision-making, fostering a dynamic and inclusive culture. They are looking for individuals who thrive in autonomous work environments, contribute meaningfully to shared success, and embrace growth both personally and professionally. They are a fully remote team that gets together for periodic in-person events to keep collaboration strong. About the Role Our partner is hiring a Data Engineer to help build and operate the pipelines that power their mobile marketing platform. You'll join a hands-on team that owns everything from the real-time event ingestion that captures user activity to the warehouse models that drive reporting and decision-making. This is a great fit for someone with a couple of years of pipeline experience who's ready to take ownership of meaningful systems and grow into broader infrastructure work over time. They do not ask anyone to specialize too narrowly; you'll have room to learn the parts of the stack you're most curious about. What You'll Work On Build and maintain Airflow DAGs that orchestrate data ingestion, transformation, and reporting across the platform Author and tune dbt models that turn raw event data into the tables analysts and partners rely on Operate and improve partner-facing event ingestion: postback endpoints, queue-based processing, dead-letter handling, and replays Integrate with mobile measurement partners (AppsFlyer, Adjust, Tune, Singular) and other vendor APIs to bring their data into the warehouse Contribute to AWS infrastructure (Lambda, SQS, DynamoDB, S3) that supports pipelines, with opportunities to learn CDK and infrastructure-as-code Collaborate with engineering, analytics, and operations teams to scope, ship, and support data work end to end Tech Stack Orchestration & transformation: Airflow (MWAA), dbt Languages: Python, SQL, with some TypeScript on the infrastructure side Cloud: AWS (Lambda, SQS, DynamoDB, S3, Redshift) Infrastructure: AWS CDK (TypeScript) Other: Flask for partner-facing service endpoints, Postgres for application data Required 2+ years of professional experience building and shipping data pipelines Strong SQL skills and comfort working with relational databases Proficient in Python, with experience writing production code Hands-on experience with a cloud platform (AWS preferred) Familiarity with a transformation framework like dbt, or willingness to ramp on one quickly Comfortable owning the operational side of data work: debugging failed jobs, handling retries, monitoring, and alerting Strong communication skills and willingness to collaborate across engineering, analytics, and operations Nice to Have Experience with Airflow or another DAG-based orchestrator Background in AdTech, mobile marketing, or attribution, particularly familiarity with postback flows or mobile measurement partners (AppsFlyer, Adjust, Tune, Singular, Branch) Exposure to infrastructure-as-code (CDK, Terraform, CloudFormation) Experience with queue-based or event-driven systems (SQS, Kafka, Pub/Sub) Experience with Flask or another Python web framework A degree in computer science, statistics, information systems, or another quantitative field is welcome but not required. They care more about what you've built and shipped than where you went to school.