Data Engineer
職務内容
2 days ago
2 Years of experience Remote
Description
About the Client
Founded in 2013, the client is a leader in performance-based mobile app marketing, partnering globally to deliver premium users at scale. Our collaborative team prioritizes innovation and strategic decision making, fostering a dynamic and inclusive culture. We're looking for individuals who thrive in autonomous work environments, contribute meaningfully to shared success, and embrace growth both personally and professionally.
We're a fully remote team that gets together for periodic in-person events to keep collaboration strong.
About The Role The client is hiring a Data Engineer to help build and operate the pipelines that power our 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 our 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. We don't 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 our analysts and partners rely on
- Operate and improve our 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 our warehouse
- Contribute to AWS infrastructure (Lambda, SQS, DynamoDB, S3) that supports our 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
- 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
- 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
- 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
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