Associate Staff Engineer - Data Engineer
Guadalajara, Mexico
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign scalable Snowflake data models using star, snowflake, OBT and Data Vault patterns
Build, test and document dbt models across staging, intermediate and mart layers
Monitor and optimize Snowflake compute and storage costs
Build ELT/ETL pipelines from ERP, MES, IoT, API and flat-file sources
Implement data quality checks, lineage tracking and documentation standards
From the employer’s posting
Architect and develop scalable, performant data models in Snowflake using dimensional modeling (star/snowflake schemas), OBT, and Data Vault patterns
Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers
Monitor and optimize Snowflake compute and storage costs
Design and build robust ELT/ETL data pipelines to ingest, transform, and deliver data from diverse sources (ERP, MES, IoT, APIs, flat files)
Implement data quality checks, lineage tracking, and documentation standards
Tools in this posting
- Python
- SQL
- AWS
- Azure
- dbt
- GCP
- Power BI
- Snowflake
- Tableau
Source — Tool mentions in context
- Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend. - Data Pipeline Development: Design and build robust ELT/ETL data pipelines to ingest, transform, and deliver data from diverse sources (ERP, MES, IoT, APIs, flat files) into Snowflake/ AWS Glue/ Lambda. Automate workflows using orchestration tools and Python scripting. - Data Quality & Governance: Implement data quality checks, lineage tracking, and documentation standards. Champion data governance practices to ensure trusted, reliable data across the organization.
- Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries. - Proficiency in Python for data pipeline development, automation, scripting, and API integrations. - Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations.
- Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration. - Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries. - Proficiency in Python for data pipeline development, automation, scripting, and API integrations.
Qualifications Must have skills: Cloud development (Strong), DBT, SQL (Expert), Snowflake Company Description
- Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations. - Cloud platform experience (Azure, AWS, or GCP) including storage, compute, networking, and infrastructure-as-code basics. Qualifications
- Design & Build Data Models: Architect and develop scalable, performant data models in Snowflake using dimensional modeling (star/snowflake schemas), OBT, and Data Vault patterns. You''''ll own the data warehouse layer that powers analytics and reporting across the organization. - Develop & Maintain dbt Projects: Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers. Enforce best practices including version control, CI/CD, data contracts, and comprehensive testing (schema, data, and freshness tests). - Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend.
Expectation from the Candidate: - Experience: 3+ years of experience in data engineering, analytics engineering, or a related role, with hands-on Snowflake and dbt experience in a production environment. - Technical Prowess:- Expert-level Snowflake skills: data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams/tasks, data sharing, and cost management.
- Technical Prowess:- Expert-level Snowflake skills: data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams/tasks, data sharing, and cost management. - Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration. - Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries.
- Proficiency in Python for data pipeline development, automation, scripting, and API integrations. - Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations. - Cloud platform experience (Azure, AWS, or GCP) including storage, compute, networking, and infrastructure-as-code basics.
Role and Responsibility: - Design & Build Data Models: Architect and develop scalable, performant data models in Snowflake using dimensional modeling (star/snowflake schemas), OBT, and Data Vault patterns. You''''ll own the data warehouse layer that powers analytics and reporting across the organization. - Develop & Maintain dbt Projects: Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers. Enforce best practices including version control, CI/CD, data contracts, and comprehensive testing (schema, data, and freshness tests).
- Develop & Maintain dbt Projects: Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers. Enforce best practices including version control, CI/CD, data contracts, and comprehensive testing (schema, data, and freshness tests). - Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend. - Data Pipeline Development: Design and build robust ELT/ETL data pipelines to ingest, transform, and deliver data from diverse sources (ERP, MES, IoT, APIs, flat files) into Snowflake/ AWS Glue/ Lambda. Automate workflows using orchestration tools and Python scripting.
- Experience: 3+ years of experience in data engineering, analytics engineering, or a related role, with hands-on Snowflake and dbt experience in a production environment. - Technical Prowess:- Expert-level Snowflake skills: data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams/tasks, data sharing, and cost management. - Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration.
Posting record
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- Live
- First seen by us
- Oct 14, 2026 · 15 days ago
- Recorded sightings
- 50
- Last seen by us
- Oct 30, 2026
- Reposted
- once since Sep 30, 2026
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Job description
Job Description
Role and Responsibility:
- Design & Build Data Models: Architect and develop scalable, performant data models in Snowflake using dimensional modeling (star/snowflake schemas), OBT, and Data Vault patterns. You''''ll own the data warehouse layer that powers analytics and reporting across the organization.
- Develop & Maintain dbt Projects: Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers. Enforce best practices including version control, CI/CD, data contracts, and comprehensive testing (schema, data, and freshness tests).
- Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend.
- Data Pipeline Development: Design and build robust ELT/ETL data pipelines to ingest, transform, and deliver data from diverse sources (ERP, MES, IoT, APIs, flat files) into Snowflake/ AWS Glue/ Lambda. Automate workflows using orchestration tools and Python scripting.
- Data Quality & Governance: Implement data quality checks, lineage tracking, and documentation standards. Champion data governance practices to ensure trusted, reliable data across the organization.
Expectation from the Candidate:
- Experience: 3+ years of experience in data engineering, analytics engineering, or a related role, with hands-on Snowflake and dbt experience in a production environment.
- Technical Prowess:
- Expert-level Snowflake skills: data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams/tasks, data sharing, and cost management.
- Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration.
- Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries.
- Proficiency in Python for data pipeline development, automation, scripting, and API integrations.
- Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations.
- Cloud platform experience (Azure, AWS, or GCP) including storage, compute, networking, and infrastructure-as-code basics.
Qualifications
Must have skills: Cloud development (Strong), DBT, SQL (Expert), Snowflake
Company Description
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Source details
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- Pay
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- Location & working pattern
Guadalajara, Mexico
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