4Bell Technology
Full Stack Data Engineer(R-1513)
3,000,000.00-3,600,000.00/A
Any Degree
IT (Information Technology)
Full-time
Mumbai
22-Oct-2026
Job Description
-
·
Develop and maintain
Snowflake-based data products and data models.
·
Build and manage ELT
pipelines using dbt and modern data engineering practices.
·
Implement automated data
quality checks, monitoring and observability across data pipelines.
·
Deliver reliable, secure
and well-governed datasets for analytics and operational use cases.
·
Collaborate with Product
Managers, Analysts and Business Stakeholders to understand data requirements
and deliver fit-for-purpose solutions.
·
Design solutions with
scalability, maintainability, performance and cost optimisation in mind.
·
Support real-time and
near-real-time data integration patterns using Kafka and event-driven
architectures.
·
Develop reusable
frameworks, standards and engineering best practices across the data platform.
·
Implement CI/CD
pipelines and automated deployment processes.
·
Troubleshoot and resolve
data quality, performance and reliability issues.
·
Contribute to platform
modernisation and continuous improvement initiatives.
·
Work closely with Data
Governance teams to ensure compliance with GDPR, security and data management
standards.
·
Participate in code
reviews and promote engineering excellence across the team.
·
Mentor junior engineers
and contribute to knowledge sharing across the Data & Analytics community.
·
Evaluate emerging
technologies and recommend improvements to the platform and engineering
practices.
·
Support AI and advanced
analytics initiatives through the delivery of trusted, high-quality data assets
Data Engineering
- Advanced SQL
- Python
- Data Modelling (Dimensional Modelling, Kimball,
Data Vault fundamentals)
- ELT/ETL design and development
- Data Warehousing concepts
- Data Lakehouse concepts
- Data Quality Engineering
- Snowflake
- dbt
- Git
- CI/CD pipelines
- Data Observability and Monitoring
- AWS fundamentals
- Infrastructure as Code (Terraform)
- APIs and data integrations
- Containerisation fundamentals (Docker)
- Kafka fundamentals
- Event-Driven Architecture concepts
- CDC (Change Data Capture) concepts
- Agile delivery (Scrum/Kanban)
- Test-driven engineering principles
- Code review practices
- Performance optimisation
- Cost optimisation