Data Engineer

• 1-5 years of experience in building and maintaining robust data pipelines, enriching data, low-latency/highly-performance data analytics applications.
• Experience handling complex, high volume, multi-dimensional data and architecting data products in streaming, serverless, and microservices-based Architecture and platform.
• Experience in Data warehousing, Data modeling, and Data architecture.
• Expert level proficiency with the relational and NoSQL databases.
• Expert level proficiency in Python, and PySpark.
• Familiarity with Big Data technologies and utilities (Spark, Hive, Kafka, Airflow).
• Familiarity with cloud services (preferable AWS)
• Familiarity with MLOps processes such as data labeling, model deployment, data-model feedback loop, data drift.

Key Roles/Responsibilities:

• Act as a technical leader for resolving problems, with both technical and non-technical audiences.
• Identifying and solving issues with data pipelines regarding consistency, integrity, and completeness.
• Lead data initiatives, architecture design discussions, and implementation of next-generation BI solutions.
• Partner with data scientists, tech architects to build advanced, scalable, efficient self-service BI infrastructure.
• Provide thought leadership and mentor data engineers in information presentation and delivery.