Data Engineer – Snowflake, DBT

Job not on LinkedIn

🕒 June 25

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 33%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Everest Technologies, Inc

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1997

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Everest Technologies, Inc. is a technology solutions provider that focuses on addressing business challenges through innovative IT services. The company specializes in managed services, project solutions, and staff augmentation, helping organizations improve their engineering capabilities and enhance their operational efficiency. Everest Technologies leverages advanced methodologies in DevOps, quality engineering, and cloud enablement, offering a wide range of application services to drive technology transformations across various industries.

📋 Description

• Design, develop, and maintain robust data transformation pipelines using dbt (Data Build Tool) to implement version-controlled, tested, and documented data models. • Architect, manage, and optimize enterprise-scale data warehouses within Snowflake, ensuring optimal storage, compute sizing, clustering, and data sharing strategies. • Build scalable ingestion pipelines to extract data from various enterprise source systems (such as ERPs like SAP or Oracle, CRM platforms, and operational databases) and load it into Snowflake. • Troubleshoot and fine-tune complex SQL queries, dbt models, and Snowflake warehouse utilization to improve execution speeds and manage costs efficiently. • Establish rigorous data quality checks, testing frameworks (using dbt test configurations), and data monitoring patterns to ensure enterprise data reliability and lineage accuracy. • Implement and maintain best practices for modern data stack workflows, utilizing Git and CI/CD pipelines (e.g., GitHub Actions, GitLab CI) for seamless deployment of data models.

🎯 Requirements

• 5+ years of dedicated data engineering experience, with a heavy emphasis on data warehouse modeling and pipeline development. • In-depth, production-level experience with Snowflake architecture, Snowpipe, tasks, streams, cloning, and secure data sharing. • Advanced proficiency with dbt Core or dbt Cloud, macros, packages, and custom testing strategies. • Expert-level mastery of SQL (complex joins, window functions, and query optimization techniques). • Strong working knowledge of Python or Scala for building custom data utilities or ingestion scripts. • Strong command of Git workflows for collaborative data modeling and code reviews. • Familiarity operating within Agile/Scrum delivery environments with a clear understanding of DevOps/DataOps principles. • Prior experience in heavy manufacturing, building materials, logistics, or infrastructure domains. • Certifications such as SnowPro Core / Advanced or dbt Certified Developer. • Experience with orchestration tools such as Apache Airflow, Prefect, or Dagster. • Familiarity with cloud platforms (AWS, Azure, or GCP) and cloud-native data security principles.