Thakral One Hiring! Full Time Data Engineer in Federal Territory - Ricebowl

As a Data Engineer, you will design, build, and maintain modular data pipelines that support efficient refresh cycles, integrate AI/ML models, and ensure reliable, scalable, and secure data environments. You will collaborate with cross‑functional teams to deliver high‑quality data solutions that meet business and operational needs.

What You’ll Do and How You’ll Succeed

Data Pipeline Development

• Design, develop, and maintain pipelines using Airflow.
• Build modular and incremental data flows to optimise refresh cycles and minimise redundant runs.
• Develop ETL/ELT workflows to ingest and transform data from telecom and operational systems.
• Integrate APIs and external data sources into pipelines.

AI/ML Integration & Governance

• Collaborate with cross‑functional teams to integrate AI/ML models into production environments.
• Ensure data quality, version control, and governance through documentation and reusable components.
• Contribute to domain logic validation with business and analytics teams.

Optimisation & Troubleshooting

• Participate in troubleshooting and optimisation of data processes.
• Ensure reliability, scalability, and performance of data workflows.
• Implement best practices for access management and governance.

We’d Love to Hear From You If...

Experience

• You have 3–7 years of hands‑on experience in data engineering or related roles.
• You have experience designing incremental and modular pipelines.
• You have experience integrating APIs and external data sources.

Technical Expertise

• You have strong proficiency in Python, SQL, and modern frameworks (Airflow, Spark).
• You have working knowledge of Azure data ecosystem (Data Factory, AzureML, Synapse, Blob Storage, Azure SQL).
• You have familiarity with AWS services (S3, ECS, RDS, EC2).
• You have strong understanding of data governance, versioning, and access management.

Ways of Working

• You solve problems with structured thinking and clear communication.
• You collaborate effectively with business, analytics, and engineering teams.
• You balance technical depth with delivery timelines and operational reliability.