Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)
Skills
GCp
Python
Data engineer
Git and GitHub
BigQuery
Cloud Dataflow
ETL
Job Details
What you ll do
- Develop and enhance Python frameworks and libraries to support data processing, quality, lineage, governance, analysis, and machine learning operations.
- Design, build, and maintain scalable and efficient data pipelines on Google Cloud Platform.
- Implement robust monitoring, logging, and alerting systems to ensure the reliability and stability of data infrastructure.
- Build scalable batch pipelines leveraging Big query, Dataflow and Airflow/Composer scheduler/executor framework on Google Cloud Platform
- Building data pipelines, leveraging Scala, Pub Sub, Akka, Dataflow on Google Cloud Platform
- Design our data models for optimal storage and retrieval and to meet machine learning modeling using technologies like Bigtable and Vertex Feature Store
- Contribute to shared Data Engineering tooling & standards to improve the productivity and quality of output for Data Engineers across the company
Minimum Basic Requirements
- Python Expertise: Write and maintain Python frameworks and libraries to support data processing and integration tasks.
- Code Management: Use Git and GitHub for source control, code reviews, and version management.
- Google Cloud Platform Proficiency: Extensive experience working with Google Cloud Platform services (e.g., BigQuery, Cloud Dataflow, Pub/Sub, Cloud Storage).
- Python Mastery: Proficient in Python with experience in writing, maintaining, and optimizing data processing frameworks and libraries.
- Software Engineering: Strong understanding of software engineering best practices, including version control (Git), collaborative development (GitHub), code reviews, and CI/CD.
- Data Management: Deep knowledge of data modeling, ETL/ELT, and data warehousing concepts.
- Problem-Solving: Excellent problem-solving skills with the ability to tackle complex data engineering challenges.
- Communication: Strong communication skills, including the ability to explain complex technical details to non-technical stakeholders.
- Data Science Stack: Proficiency in data analysis and familiarity with tools such as Jupyter Notebook, pandas, NumPy, and other Python data analysis libraries.
- Frameworks/Tools: Familiarity with machine learning and data processing tools and frameworks such as TensorFlow, Apache Spark, and scikit-learn.
- Bachelor s or master s degree in computer science, Engineering, Computer Information Systems, Mathematics, Physics, or a related field or software development training program
Preferred Qualifications
- Experience in Scala, Java, and/or any functional language. We code primarily in Scala, so you ll be excited to either ramp or continue with such
- Experience in microservices architecture, messaging patterns, and deployment models
- Experience in API design and building robust and extendable client/server contracts
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