Sr Snowflake and dbt Developer

hace 1 mes

guadalajara, México Aitopics A tiempo completo

At Meztal, we are dedicated to harnessing the power of data to drive informed decision-making and innovative solutions. We are seeking a highly skilled Senior Snowflake and dbt Developer to join our dynamic data engineering team. This role requires a strong command of English, as you will collaborate with diverse stakeholders across our international operations.

Key Responsibilities:

Data Architecture and Modeling:
  • Design and implement data models within Snowflake using dbt to support analytics, reporting, and machine learning use cases.
  • Develop and maintain scalable, optimized data architectures, including star and snowflake schemas, ensuring data lineage for accuracy and transparency.
  • Build, schedule, and manage ETL/ELT pipelines in dbt to extract, transform, and load data into Snowflake.
  • Optimize data ingestion, transformation, and aggregation processes to ensure low latency and high data availability.
Data Quality and Governance:
  • Implement data validation and testing frameworks within dbt to ensure data accuracy and quality, utilizing dbt tests, documentation, and snapshots.
  • Collaborate with the data governance team to ensure compliance, security, and adherence to company-wide data standards.
Performance Tuning and Optimization:
  • Enhance performance within Snowflake through advanced techniques, including clustering, partitioning, caching, and query optimization.
  • Regularly monitor dbt model performance and make necessary adjustments for efficiency and cost optimization.
Collaboration and Cross-functional Support:
  • Partner with data analysts, data scientists, and business units to understand data requirements and deliver accessible, usable data assets.
  • Act as the subject matter expert in Snowflake and dbt, guiding best practices and ensuring solutions align with strategic goals.
Documentation and Best Practices:
  • Create and maintain comprehensive documentation for dbt models, Snowflake architecture, and data transformation processes.
  • Establish best practices for development, deployment, and version control within dbt and Snowflake, supporting code reviews and continuous improvement.
Troubleshooting and Support:
  • Provide support for data pipeline issues, Snowflake performance, and dbt run-time errors.
  • Collaborate with the data engineering team to resolve data quality issues, troubleshoot data discrepancies, and implement fixes.

Requirements

Required Skills and Experience:

  • Snowflake Expertise: Advanced knowledge of Snowflake features (SQL, views, data sharing, time travel, zero-copy cloning) and hands-on experience with managing large Snowflake environments.
  • dbt Proficiency: Extensive experience with dbt, including model development, testing, documentation, macros, and configurations, with a solid understanding of dbt best practices.
  • SQL Mastery: Expert-level SQL skills for writing efficient queries, data transformations, and Snowflake stored procedures.
  • Data Pipeline and Orchestration: Experience with data pipeline tools such as Apache Airflow, Prefect, or similar, and familiarity with scheduling and orchestrating dbt models.
  • Data Modeling: Strong knowledge of data modeling concepts (star, snowflake schemas) and the ability to design models for high performance and scalability.
  • Cloud Platforms: Familiarity with cloud data ecosystems (e.g., Azure, AWS, or GCP) and integration of cloud storage solutions (like S3 or Azure Blob) with Snowflake.
  • Version Control and CI/CD: Experience with version control (e.g., Git) and CI/CD practices for deploying and managing dbt projects.
  • Soft Skills: Excellent communication and collaboration skills, particularly in professional English, to work effectively with technical and non-technical stakeholders. Strong problem-solving abilities and the capacity to work independently with minimal supervision.

Preferred Qualifications:

  • Experience with BI tools (e.g., Looker, Power BI, Tableau) for data visualization.
  • Knowledge of Python or other scripting languages for automation tasks within data workflows.
  • Familiarity with data governance and compliance frameworks.
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