Data Infrastructure Engineer
hace 5 días
MonetizeMore is a global leader in ad tech, helping publishers maximize their ad revenue through advanced optimization, data, and automation. Our fully remote team is distributed across the world, driven by innovation, autonomy, and measurable impact.
Role OverviewWe are looking for a Data Infrastructure Engineer to design, build, and maintain scalable data systems that support analytics, machine learning, and business intelligence at MonetizeMore. You will collaborate closely with data engineers, analysts, and product teams to ensure our data pipelines are reliable, efficient, and secure.
In addition to core data infrastructure responsibilities, you will occasionally work on Airflow DAGs and orchestration tasks, supporting our data workflow automation initiatives.
Key Responsibilities- Design, implement, and maintain scalable, high-performance data infrastructure.
- Manage the data pipelines using Apache Airflow for orchestration and scheduling.
- Develop and deploy data services and tools using Kubernetes and containerized environments.
- Leverage AWS services (e.g., S3, Lambda, Athena, ECS/EKS, Glue) for data storage, processing, and orchestration.
- Ensure reliability, performance, and cost efficiency of data systems.
- Collaborate with cross-functional teams to support data-driven initiatives and ad tech systems.
- Implement monitoring, logging, and alerting for all critical data infrastructure components.
- Champion best practices in data security, governance, and DevOps for data workflows.
Required:
- 1-2 years of experience in data infrastructure roles.
- Strong proficiency with Python and SQL.
- Solid understanding of AWS data and compute services (S3, Athena, ECS/EKS, etc.).
- Experience in CI/CD, infrastructure-as-code (Terraform, CloudFormation, or similar).
- Experience with containerization (Docker).
- Strong problem-solving and debugging skills.
- Experience with transactional database maintenance. Preferred: Postgres
Preferred:
- Knowledge of data warehousing tools like Athena, or BigQuery.
- Experience managing workflows with Apache Airflow.
- Hands-on experience deploying and maintaining workloads on Kubernetes.
- Familiarity with real-time data streaming (Kafka, Kinesis, etc.).
- Exposure to monitoring and observability tools (Prometheus, Grafana, ELK Stack).
- 100% remote, flexible work environment.
- Work with cutting-edge ad tech and data systems.
- Collaborative, globally distributed team.
- Opportunities for growth and ownership.
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