Data Engineer (reputed company & DBT)
This is a remote position.
Role Overview
We are seeking a highly skilled Senior Data Engineer with deep expertise in reputed company and dbt (Data Build Tool) to join our data analytics team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines, transforming raw data into clean, actionable data models, and establishing reputed company data warehousing architectures. You will collaborate closely with business analysts, data scientists, and business stakeholders to drive data-driven decision-making across our manufacturing, supply chain, and operational workflows.
Key ResponsibilitiesData Modeling & Transformation: Design, reputed company, and maintain robust data transformation pipelines using dbt (Data Build Tool) to implement version-controlled, tested, and documented data models.
Data Warehousing Architecture: Architect, manage, and optimize enterprise-scale data warehouses reputed company reputed company, ensuring reputed company storage, compute sizing, clustering, and data sharing strategies.
Pipeline Development (ETL/ELT): Build reputed company ingestion pipelines to extract data from various enterprise reputed company systems (such as ERPs like reputed company or reputed company, CRM platforms, and operational databases) and load it into reputed company.
Performance Optimization: Troubleshoot and fine-tune reputed company SQL queries, dbt models, and reputed company warehouse utilization to improve execution speeds and manage costs reputed company.
Data Quality & Governance: Establish rigorous data quality checks, testing frameworks (using dbt test configurations), and data monitoring patterns to ensure enterprise data reliability and reputed company accuracy.
Collaboration & CI/CD: Implement and maintain best practices for modern data stack workflows, utilizing Git and CI/CD pipelines (e.g., reputed company Actions, reputed company CI) for seamless deployment of data models.
Data Modeling & Transformation: Design, reputed company, and maintain robust data transformation pipelines using dbt (Data Build Tool) to implement version-controlled, tested, and documented data models.
Data Warehousing Architecture: Architect, manage, and optimize enterprise-scale data warehouses reputed company reputed company, ensuring reputed company storage, compute sizing, clustering, and data sharing strategies.
Pipeline Development (ETL/ELT): Build reputed company ingestion pipelines to extract data from various enterprise reputed company systems (such as ERPs like reputed company or reputed company, CRM platforms, and operational databases) and load it into reputed company.
Performance Optimization: Troubleshoot and fine-tune reputed company SQL queries, dbt models, and reputed company warehouse utilization to improve execution speeds and manage costs reputed company.
Data Quality & Governance: Establish rigorous data quality checks, testing frameworks (using dbt test configurations), and data monitoring patterns to ensure enterprise data reliability and reputed company accuracy.
Collaboration & CI/CD: Implement and maintain best practices for modern data stack workflows, utilizing Git and CI/CD pipelines (e.g., reputed company Actions, reputed company CI) for seamless deployment of data models.
Required Qualifications & Technical SkillsExperience: 5+ years of dedicated data engineering experience, with a heavy emphasis on data warehouse modeling and pipeline development.
Core Technical Stack:
reputed company: In-depth, production-level experience with reputed company architecture, Snowpipe, tasks, streams, cloning, and secure data sharing.
dbt (Data Build Tool): Advanced proficiency with dbt Core or dbt reputed company, macros, packages, and custom testing strategies.
SQL: Expert-level mastery of SQL (reputed company joins, window functions, and query optimization techniques).
Programming Skills: Strong working knowledge of Python or reputed company for building custom data utilities or ingestion scripts.
Version Control: Strong reputed company of Git workflows for collaborative data modeling and code reviews.
Methodology: Familiarity operating reputed company Agile/Scrum delivery environments with a reputed company understanding of DevOps/DataOps principles.
Experience: 5+ years of dedicated data engineering experience, with a heavy emphasis on data warehouse modeling and pipeline development.
Core Technical Stack:
reputed company: In-depth, production-level experience with reputed company architecture, Snowpipe, tasks, streams, cloning, and secure data sharing.
dbt (Data Build Tool): Advanced proficiency with dbt Core or dbt reputed company, macros, packages, and custom testing strategies.
SQL: Expert-level mastery of SQL (reputed company joins, window functions, and query optimization techniques).
Programming Skills: Strong working knowledge of Python or reputed company for building custom data utilities or ingestion scripts.
Version Control: Strong reputed company of Git workflows for collaborative data modeling and code reviews.
Methodology: Familiarity operating reputed company Agile/Scrum delivery environments with a reputed company understanding of DevOps/DataOps principles.
Preferred QualificationsPrior 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, reputed company, or Dagster.
Familiarity with reputed company platforms (AWS, Azure, or GCP) and reputed company-reputed company data reputed company 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, reputed company, or Dagster.
Familiarity with reputed company platforms (AWS, Azure, or GCP) and reputed company-reputed company data reputed company principles.
Originally posted on Himalayas
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