Senior Data Engineer (Snowflake, AWS, dbt, SQL &

- Python)Experience: 8–14 Years | Location: PAN India

- Role OverviewWe are looking for an experienced Data Engineer with strong hands-on expertise in Snowflake, AWS, dbt, SQL, and Python. The candidate will be responsible for designing, developing, and maintaining scalable data pipelines and cloud-based data warehouse solutions.
- Data Engineering &
- Pipeline Development
- Design, develop, and maintain scalable data pipelines using Snowflake, AWS, dbt, SQL, and Python.
- Develop reliable ETL/ELT pipelines to ingest, transform, validate, and load data from multiple sources.
- Implement data transformations using advanced SQL and Python, including incremental loads, Change Data Capture (CDC), Slowly Changing Dimensions (SCD Type 1/2), and complex business rules.
3.

Snowflake Data

Warehousing

- Build and optimize cloud-based data warehouse solutions on Snowflake.
- Work on Snowflake schemas, tables, views, stages, streams, tasks, and stored procedures.
- Apply Snowflake performance optimization practices, including warehouse optimization and cost management.
- Ensure efficient and scalable data warehouse solutions.

4. dbt Development &
- Data Transformation
- Create reusable and modular dbt models, macros, tests, snapshots, and documentation.
- Maintain data lineage and ensure proper documentation of data transformations.
- Develop and manage data transformation workflows using dbt.

5. AWS Cloud Services
- Work with AWS services such as:
- Amazon S3
- AWS Glue
- AWS Lambda
- AWS IAM
- Amazon CloudWatch
- AWS Step Functions
- Utilize these services to support data ingestion, processing, orchestration, and monitoring.

6.



Data Quality &
- Data Governance

- Implement data-quality checks covering:
- Completeness
- Accuracy
- Consistency
- Uniqueness
- Reconciliation
- Referential Integrity
- Apply data governance and security practices.
- Implement role-based access control, data masking, and row-level security.
- Ensure data quality, governance, and lineage across data pipelines and warehouse solutions.

7. CI/CD &
- Development Practices

- Develop and maintain CI/CD pipelines using Git-based tools such as:
- GitHub Actions
- GitLab CI
- Jenkins
- Azure DevOps
- Work with Git, code reviews, and branching strategies.
- Implement automated testing and follow established development practices.

8.

Stakeholder

Collaboration

- Collaborate with Data Architects, Business Analysts, application teams, and other stakeholders.
- Work closely with technical and business teams to deliver governed data products.
- Support effective coordination throughout the data engineering and delivery lifecycle.

9.

Mandatory

Skills &

- Experience
- 7+ years of experience in Data Engineering, Data Warehousing, or Cloud Data Platforms.
- Strong hands-on experience with Snowflake, AWS, dbt, SQL, and Python.
- Proven experience designing and developing ETL/ELT pipelines and cloud data warehouse solutions.
- Strong understanding of data modelling, dimensional modelling, and Star Schema.
- Solid knowledge of data quality, data governance, and data lineage.
- Experience with Git, code reviews, branching strategies, automated testing, and CI/CD.
- Good understanding of Agile delivery, production support, incident resolution, and technical documentation.

📌 Lead Snowflake Data Engineer (AWS, dbt, SQL & Python) (India)
🏢 Rabi Solutions
📍 India