Posted on: 26/03/2026
Description :
Key Responsibilities :
- 1. Design and implement scalable ELT pipelines using dbt on Snowflake, following industry accepted best practices.
- 2. Build ingestion pipelines from various sources including relational databases, APIs, cloud storage and flat files into Snowflake.
- 3. Implement data modelling and transformation logic to support layered architecture (e.g., staging, intermediate, and mart layers or medallion architecture) to enable reliable and reusable data assets..
- 4. Leverage orchestration tools (e.g., Airflow,dbt Cloud, or Azure Data Factory) to schedule and monitor data workflows.
- 5. Apply dbt best practices : modular SQL development, testing, documentation, and version control.
- 6. Perform performance optimizations in dbt/Snowflake through clustering, query profiling, materialization, partitioning, and efficient SQL design.
- 7. Apply CI/CD and Git-based workflows for version-controlled deployments.
- 8. Contribute to growing internal knowledge base of dbt macros, conventions, and testing frameworks.
- 9. Collaborate with multiple stakeholders such as data analysts, data scientists, and data architects to understand requirements and deliver clean, validated datasets.
- 10. Write well-documented, maintainable code using Git for version control and CI/CD processes.
- 11. Participate in Agile ceremonies including sprint planning, stand-ups, and retrospectives.
- 12. Support consulting engagements through clear documentation, demos, and delivery of client-ready solutions.
Required Qualifications :
- 3 to 5 years of experience in data engineering roles, with 2+ years of hands-on experience in Snowflake and DBT or Matillion (Matillion-DPC is highly preferred, not mandatory
- Experience building and deploying DBT models in a production environment.
- Expert-level SQL and strong understanding of ELT principles. Strong understanding of ELT patterns and data modelling (Kimball/Dimensional preferred).
- Familiarity with data quality and validation techniques : dbt tests, dbt docs etc.
- Experience with Git, CI/CD, and deployment workflows in a team setting
- Familiarity with orchestrating workflows using tools like dbt Cloud, Airflow, or Azure Data Factory.
Core Competencies :
- Data Engineering and ELT Development :
- Building robust and modular data pipelines using dbt.
- Writing efficient SQL for data transformation and performance tuning in Snowflake.
- Managing environments, sources, and deployment pipelines in dbt.
- Cloud Data Platform Expertise :
- Strong proficiency with Snowflake : warehouse sizing, query profiling, data loading, and performance optimization.
- Experience working with cloud storage (Azure Data Lake, AWS S3, or GCS) for ingestion and external stages.
Technical Toolset :
- Languages & Frameworks :
- Python : For data transformation, notebook development, automation.
- SQL : Strong grasp of SQL for querying and performance tuning.
Best Practices and Standards :
- Knowledge of modern data architecture concepts including layered architecture (e.g., staging ? intermediate ? marts, Matillion architecture).
- Familiarity with data quality, unit testing (dbt tests), and documentation (dbt docs).
Security & Governance :
- Access and Permissions :
- Understanding of access control within Snowflake (RBAC), role hierarchies, and secure data handling.
- Familiar with data privacy policies (GDPR basics), encryption at rest/in transit.
Deployment & Monitoring :
- DevOps and Automation :
- Version control using Git, experience with CI/CD practices in a data context.
- Monitoring and logging of pipeline executions, alerting on failures.
Soft Skills :
- Communication & Collaboration :
- Ability to present solutions and handle client demos/discussions.
- Work closely with onshore and offshore team of analysts, data scientists, and architects.
- Ability to document pipelines and transformations clearly.
- Basic Agile/Scrum familiarity working in sprints and logging tasks.
- Comfort with ambiguity, competing priorities and fast-changing client environment.
Education :
- Bachelors or masters degree in computer science, Data Engineering, or a related field.
- Certifications such as Snowflake SnowPro, dbt Certified Developer Data Engineering are a plus.
Please note the mandatory or most preferred skill set for this role
- Must have experience in Snowflake
- Must have experience in DBT or Matillion (Matillion-DPC is highly preferred)
- Must have experience in SSIS
Required Qualification :
- Bachelor of Engineering - Bachelor of Technology (B.E./B.Tech.) ,
- We need only immediate joiners
- Communication should be excellent
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1623707