Senior Data Transformation Specialist

1 day ago

Nagpur, Maharashtra, India beBeeDataEngineer Full time ₹ 15,00,000 - ₹ 20,00,000

As a key player in our Data Engineering team, you will be responsible for designing and implementing scalable data transformation pipelines using dbt on Snowflake.

Data Engineer

We are looking for an experienced professional who is proficient in building high-performance data transformation pipelines using Snowflake and dbt. The ideal candidate will have a strong understanding of ELT principles and experience with data quality and validation techniques.

  • We require 3 to 5 years of experience in data engineering roles, with 2+ years of hands-on experience in Snowflake and dbt.
  • The successful candidate will have expert-level SQL skills and be familiar with orchestration tools like dbt Cloud, Airflow, or Azure Data Factory.
  • You will work closely with data analysts, data scientists, and data architects to understand requirements and deliver clean, validated datasets.

Key Responsibilities:

  1. Design and implement scalable data transformation pipelines using dbt on Snowflake.
  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 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.

Requirements:

  • Expert-level SQL skills.
  • Familiarity with orchestration tools like dbt Cloud, Airflow, or Azure Data Factory.
  • Experience with data quality and validation techniques.
  • Strong understanding of ELT principles.
  • Knowledge of data modelling and transformation logic.
  • Familiarity with CI/CD and Git-based workflows.
  • Ability to work closely with data analysts, data scientists, and data architects.

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