Data Engineer

Design, develop, and maintain data pipelines using Airflow

Build modular and incremental data flows that allow efficient refresh cycles and minimize redundant runs

Collaborate with cross-functional teams to integrate AI/ML models into production data environments

Develop ETL/ELT workflows to ingest and transform data from multiple telecom and operational systems

Ensure data quality, version control, and governance through consistent documentation and reusable components

Participate in troubleshooting and optimization of data processes to ensure reliability, scalability, and performance

Contribute to domain logic validation in partnership with business and analytics teams

3–7 years of hands-on experience in data engineering or related roles.

Strong proficiency in Python, SQL, and modern data frameworks (e.g., Airflow, Spark)

Working knowledge of Azure data ecosystem (Data Factory, AzureML, Synapse, Blob Storage, Azure SQL, etc.)

Familiarity with AWS services (S3, ECS, RDS, EC2)

Experience designing incremental / modular data pipelines and integrating APIs or external data sources

Strong understanding of data governance, versioning, and access management practices

Excellent problem-solving skills, structured thinking, and strong communication abilities