Job Summary:

We are seeking a highly motivated Data Engineer to design, develop, and support enterprise data warehouse and advanced analytics platforms. The ideal candidate will be responsible for building scalable data pipelines, optimizing ETL processes, and enabling data-driven decision-making through robust data architectures. This role will work closely with data scientists, analysts, and business stakeholders to support machine learning, predictive analytics, and AI initiatives while ensuring data quality, security, and compliance.

Responsibilities:

- Apply data engineering principles, technologies, and best practices to design, develop, and implement data warehouse and analytical solutions.
- Enhance, maintain, and support enterprise data warehouse, data lake, and analytics platforms.
- Develop, test, troubleshoot, and optimize ETL/ELT pipelines to ensure reliability, scalability, and performance.
- Design and implement robust data architectures that meet business, performance, and compliance requirements.
- Build and maintain batch and real-time data processing solutions.
- Support advanced analytics, machine learning, predictive modeling, and AI initiatives by delivering high-quality datasets and data pipelines.
- Collaborate with data scientists, analysts,



architects, and business teams to implement analytical solutions.
- Develop and optimize database structures, queries, and data models for reporting and analytics.
- Support data migration, integration, and modernization projects across on-premises and cloud platforms.
- Implement data security, encryption, governance, and access control mechanisms to protect organizational data assets.
- Monitor data platform performance, identify bottlenecks, and implement continuous improvements.
- Create and maintain technical documentation, data mapping, and operational procedures.
- Participate in code reviews, testing, deployment activities, and production support.

Required Qualifications

- Medium to strong hands-on experience with Data Vault 2.0 and DBT/Coalesce implementations.
- Strong hands-on experience with Snowflake, SQL, PySpark, AWS, and Airflow.
- Ownership of end-to-end ELT pipelines and data transformation frameworks.
- Experience with performance tuning, troubleshooting, and production support.
- Robust hands-on proficiency in SQL and PySpark.
- Experience with data reconciliation and source-to-target validation.

📌 Data Engineer (Hyderabad)
🏢 Qentelli
📍 Hyderabad