Data Engineer

About the role

The client, a leader in performance‑based mobile app marketing, is looking for a Data Engineer to design, build, and operate the data pipelines that power its marketing platform. This fully remote role is ideal for someone with a couple of years of experience in data engineering who wants to take ownership of end‑to‑end data workflows and expand into broader infrastructure work.

Key responsibilities

• Develop and maintain Airflow DAGs to orchestrate data ingestion, transformation, and reporting.
• Write and optimise dbt models that convert raw event streams into analytical tables.
• Operate partner‑facing event ingestion services, including postback endpoints, queue processing, dead‑letter handling, and replay mechanisms.
• Integrate data from mobile measurement partners (e.g., AppsFlyer, Adjust, Tune, Singular) via their APIs into the data warehouse.
• Contribute to AWS infrastructure components such as Lambda, SQS, DynamoDB, S3, and Redshift, with opportunities to learn CDK and IaC practices.
• Collaborate with engineering, analytics, and operations teams to scope, ship, and support data solutions from concept to production.

Required profile

• 2+ years of professional experience building and shipping data pipelines.
• Strong SQL proficiency and experience with relational databases.
• Solid Python programming skills for production‑grade code.
• Hands‑on experience with a cloud platform, preferably AWS.
• Willingness to own operational aspects of data work, including debugging, retries, monitoring, and alerting.
• Effective communication and teamwork across cross‑functional groups.

Required skills

• Airflow (MWAA) for workflow orchestration.
• dbt for data transformation.
• Python and SQL.
• TypeScript (for infrastructure code).
• AWS services: Lambda, SQS, DynamoDB, S3, Redshift.
• AWS CDK (TypeScript) for infrastructure‑as‑code.
• Flask for partner‑facing service endpoints.
• PostgreSQL for application data storage.