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Snowflake

Snowflake

Infosys
Early Applicant
  • Posted 8 hours ago
  • Be among the first 10 applicants

Job Description

Good to have skills: Airflow, Azure Data Factory, AWS Glue, Terraform, Power BI

Key Responsibilities:

  • Design, develop, and maintain Snowflake-based data warehouse solutions aligned to business and analytics needs.
  • Build and manage dbt models, including incremental loads, tests, documentation, and modular transformations.
  • Develop efficient ELT pipelines to ingest, transform, and curate data into analytics-ready datasets.
  • Optimize Snowflake performance and cost through clustering strategies, warehouse sizing, query tuning, and workload management.
  • Implement data quality checks, reconciliation processes, and monitoring to ensure trusted and consistent data outputs.
  • Collaborate with analysts and downstream consumers to translate requirements into robust data models (facts/dimensions) and marts.
  • Support release management for data changes, ensuring version control, code reviews, and reliable deployments.
  • Troubleshoot data issues end-to-end, performing root-cause analysis and implementing preventive fixes. Minimum Qualifications:
  • BTECH, MTECH, MCA, or MSC.
  • 3–5 years of experience in data engineering / data warehousing roles.
  • Hands-on experience with Snowflake including schema design, SQL development, and performance optimization.
  • Hands-on experience with dbt (Data build Tool) for transformations, testing, and documentation.
  • Strong SQL skills with the ability to write optimized, maintainable queries for large datasets.
  • Experience working with structured data modeling concepts and building curated layers for analytics consumption. Preferred Qualifications:
  • Experience implementing end-to-end ELT patterns using dbt best practices (macros, packages, reusable models, exposures).
  • Familiarity with dimensional modeling and designing scalable marts for BI and self-service analytics.
  • Experience with CI/CD practices for analytics engineering (automated testing, environment promotion, deployment workflows).
  • Strong understanding of data governance concepts such as lineage, access controls, and auditability in cloud data platforms.
  • Proven ability to collaborate cross-functionally, communicate clearly, and deliver high-quality data products in agile teams.

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