We are seeking an experienced Senior Data Engineer / Lead Data Engineer with solid expertise in Data Vault 2.0, DBT/Coalesce, Snowflake, PySpark, AWS, and Airflow. The ideal candidate will lead data architecture and engineering initiatives, establish data modeling standards, drive technical decision-making, and mentor engineering teams while delivering scalable and high-performance data platform solutions.

Key Responsibilities

- Design, develop, and implement enterprise-scale data platforms using Data Vault 2.0 methodology.

- Lead end-to-end implementation of DBT and/or Coalesce-based data transformation frameworks.

- Architect and build scalable data solutions on Snowflake and cloud-native platforms.

- Develop and optimize complex SQL queries, ETL/ELT pipelines, and data integration processes.

- Build and maintain data pipelines using PySpark, AWS services, and Apache Airflow.

- Lead solution design sessions, architecture reviews, and technical discussions with stakeholders.

- Define and enforce Data Vault standards, governance policies, naming conventions, and best practices.

- Conduct code reviews and ensure adherence to engineering standards and data quality requirements.

- Collaborate with business stakeholders, architects, product owners, and delivery teams to translate requirements into scalable solutions.

- Drive technical decision-making, estimation, sprint planning, and delivery execution.





- Troubleshoot performance bottlenecks and implement optimization strategies across data platforms.

- Mentor and guide junior and mid-level engineers through technical leadership and knowledge sharing.

Required Skills & Experience

- 8+ years of experience in Data Engineering and Data Warehousing.

- Strong hands-on experience with Data Vault 2.0 architecture and implementation.

- Extensive experience with DBT and/or Coalesce.

- Strong expertise in Snowflake Data Cloud.

- Advanced SQL development and performance tuning skills.

- Hands-on experience with PySpark and distributed data processing.

- Experience with AWS services (S3, Glue, Lambda, EMR, IAM, Redshift, etc.).

- Strong experience in workflow orchestration using Apache Airflow.

- Expertise in ETL/ELT design, data modeling, and data integration patterns.

- Experience leading architecture discussions, technical reviews, and large-scale data transformation programs.

- Strong communication and stakeholder management skills.

Preferred

- Data Vault 2.0 certification or relevant data architecture certifications.

- Experience with Agile/Scrum delivery methodologies.

- Knowledge of CI/CD, DevOps, and Infrastructure as Code practices.

- Experience with data governance, metadata management, and data quality frameworks.

- Exposure to modern analytics and reporting ecosystems.

📌 Senior Data Engineer (Hyderabad)
🏢 Qentelli
📍 Hyderabad