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Data Engineer
| Company | S&P Global |
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| Location | New York, NY, USA |
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| Salary | $69661 – $125000 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Junior, Mid Level |
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Requirements
- 2+ years of experience in Big Data and Data Engineering, building enterprise-level applications in a public cloud, preferably Google Cloud
- Experience building cloud-native data pipelines using Python, Apache Airflow, Apache Spark, and Apache Beam
- Working knowledge of SQL and data warehousing concepts, including PostgreSQL and BigQuery. Optionally, knowledge of Mongo and AlloyDB is a plus
- Comfortable using Azure DevOps or similar CI/CD tools, Git
- Experience with TDD, agile software development processes, and collaborating in multi-functional agile teams
- Communicate effectively with technical teams and non-technical stakeholders.
Responsibilities
- Use the latest technology to build data pipelines and integrate machine learning models
- Build and expand our data platform
- Develop applications that run on a Google Cloud-based infrastructure
Preferred Qualifications
- Experience building Docker images and deploying them to a Production environment. Integrate Docker container orchestration framework using Kubernetes by creating pods, config Maps, and deployments using terraform
- Experience with C#, .NET core, and microservices.
