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Data Engineer - Snowflake DB

Data Engineer - Snowflake DB

YO HR ConsultancyHyderabad
30+ days ago
Job description

Experience : 6 to 10 Years.

Qualifications Qualifications :

  • 5 to 8 years of experience in data engineering roles, with 3+ years of hands-on experience working with Snowflake and dbt in production environments.
  • Proven experience building and deploying dbt models in production.
  • Expert SQL skills and strong understanding of ELT principles.
  • Experience with Git, CI / CD, and team-based deployment workflows.
  • Familiarity with data quality and validation practices (e.g., dbt tests and dbt docs).

Preferred Qualifications :

  • Experience with data modeling (Kimball or dimensional approaches).
  • Familiarity with orchestration tools such as dbt Cloud, Airflow, or Azure Data Factory.
  • Experience optimizing Snowflake performance (clustering, materializations, query tuning).
  • Job Description :

    We are looking for an experienced and results-driven Data Engineer to join our growing Data Engineering team.

    The ideal candidate will be proficient in building scalable, high-performance data transformation pipelines using Snowflake and dbt and be able to effectively work in a consulting setup.

    In this role, you will be instrumental in ingesting, transforming, and delivering high-quality data to enable data-driven decision-making across the clients organization.

    Key Responsibilities :

  • Design and implement scalable ELT pipelines using dbt on Snowflake, following industry accepted best practices.
  • Build ingestion pipelines from various sources including relational databases, APIs, cloud storage and flat files into Snowflake.
  • 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.

  • Leverage orchestration tools (e.g., Airflow,dbt Cloud, or Azure Data Factory) to schedule and
  • monitor data workflows.

  • Apply dbt best practices : modular SQL development, testing, documentation, and version control.
  • Perform performance optimizations in dbt / Snowflake through clustering, query profiling,
  • materialization, partitioning, and efficient SQL design.

  • Apply CI / CD and Git-based workflows for version-controlled deployments.
  • Contribute to growing internal knowledge base of dbt macros, conventions, and testing
  • frameworks.

  • Collaborate with multiple stakeholders such as data analysts, data scientists, and data architects to understand requirements and deliver clean, validated datasets.
  • Write well-documented, maintainable code using Git for version control and CI / CD processes.
  • Participate in Agile ceremonies including sprint planning, stand-ups, and retrospectives.
  • Support consulting engagements through clear documentation, demos, and delivery of client-ready solutions.
  • (ref : hirist.tech)

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