We are looking for a Data Engineer to build and maintain scalable data pipelines and ingestion frameworks using a mix of open-source and custom-built tooling. 

You will design and operate reliable data systems that ingest, validate, and process data from APIs, databases, and event streams—ensuring high data quality, performance, and availability. 

Key Responsibilities 

Build and maintain scalable data pipelines and ingestion frameworks 

Design robust data fetching systems for APIs, databases, and streaming sources 

Ensure data quality, validation, and consistency across all pipelines 

Optimize systems for performance, scalability, and cost efficiency 

Implement observability, monitoring, and fault-tolerant architectures 

Manage batch and real-time data processing workflows 

Collaborate with platform, analytics, and product teams to deliver trusted datasets 

Contribute to data architecture, standards, and best practices 

Core Skills & Experience 

Strong experience in data engineering and distributed systems 

Proficiency in Databricks, Azure Data Factory, Python, SQL, Terraform, REST APIs.  

Experience with data pipeline tools  

Hands-on with streaming technologies  

Experience with cloud platforms  

Knowledge of data storage systems 

Understanding of data modeling, partitioning, and indexing strategies 

Experience with API integrations and event-driven architectures 

Familiarity with CI/CD and Infrastructure as Code