Full-Time Data Engineer

About the role: As a Data Engineer, you will build core infrastructure software (pipelines, APIs, data modeling, tracking events) as part of a client's data platform team. Your work includes instrumenting systems for performance and enhancement. You'll ensure data offerings are available to internal and external stakeholders with secure authentication.

Responsibilities include choosing and implementing technologies for scaling data access, batch processing, handling data from third-party suppliers, creating supporting documentation, and supplying data to researchers, considering the client's business domain knowledge.

You will also coach and mentor other engineers.

Requirements:

1. Proven experience writing maintainable and performant Python/PySpark code
2. Good understanding of Cloud environments (particularly Microsoft Azure) and data orchestration systems (e.g., Dagster, Apache Airflow)
3. Understanding of containerization (Docker) and orchestration (Kubernetes)
4. Experience with data lakes and tools like Spark or Databricks
5. Understanding of data transformation and storage formats (e.g., Apache Parquet)
6. Proficiency with version control (Git, GitHub)
7. Experience with VCL and BCL is a plus

Non-Technical Competencies:

• Strong problem-solving skills, balancing innovation with pragmatic technology choices
• Comfort in dynamic production environments and handling client expectations
• Excellent customer focus and quality mindset
• Experience working with engineering leadership and architects
• High ownership and transparency in deliverables
• Excellent communication skills

What is the last date for applying to the job?

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