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Design dimensional data models (star schema, fact and dimension tables)
Build and tune Snowflake structures with role-based access control
Build and optimize Power BI semantic models using DAX and Power Query
Improve current dashboards and propose new ones for supply chain data
Build and monitor data integration pipelines with Python and Azure Data Factory
Designs dimensional and enterprise data models (star schema, fact and dimension tables, slowly changing dimensions, surrogate keys, data marts)
Builds and tunes Snowflake structures by applying best practices in architecture, performance, and role-based access control.
Builds and optimizes Power BI semantic models with Data Analysis Expressions (DAX) and Power Query
Improves current dashboards and proposes new ones by learning supply chain data and business needs.
Builds and monitors data integration pipelines with Python and orchestration tools such as Azure Data Factory
Proven experience designing dimensional and enterprise data models (star schema, fact and dimension tables, slowly changing dimensions, surrogate keys, data marts)
Proven experience working directly with business stakeholders in requirements gathering, workshops, co-creation, and solution validation (not an order-taker profile)
Understanding of SAP data structures and extraction patterns
Proven experience building and optimizing Power BI semantic models, Data Analysis Expressions (DAX), Power Query, and enterprise-grade reports connected to a cloud data warehouse
Solid experience in agile teams and their ceremonies
Experience in the CPG industry, especially with supply chain data
From the employer’s posting.
Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 8
Similar jobs usually come down between day 6 and day 47.
From 1,409 similar postings that came down. Coming down is not always a hire.
37 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Dashboard evolution: Improves current dashboards and proposes new ones by learning supply chain data and business needs. - Data integration: Builds and monitors data integration pipelines with Python and orchestration tools such as Azure Data Factory, using standardized ingestion frameworks. - Business partnership: Gathers requirements, leads workshops, and validates solutions with client management and product leadership by co-creating solutions instead of taking orders.
- Hands-on experience with data integration pipelines in production, preferably Azure Data Factory (equivalent experience in other cloud platforms is considered), and familiarity with standardized ingestion frameworks - Advanced SQL and Python for pipelines and automation - Proven experience working directly with business stakeholders in requirements gathering, workshops, co-creation, and solution validation (not an order-taker profile)
- Proven experience building and optimizing Power BI semantic models, Data Analysis Expressions (DAX), Power Query, and enterprise-grade reports connected to a cloud data warehouse - Hands-on experience with data integration pipelines in production, preferably Azure Data Factory (equivalent experience in other cloud platforms is considered), and familiarity with standardized ingestion frameworks - Advanced SQL and Python for pipelines and automation
Nice to Have: - DevOps practices: Git, Azure DevOps, and continuous integration and delivery (CI/CD) for database change promotion - Understanding of SAP data structures and extraction patterns
- Experience with sell-in, sell-out, and retail or market research data - Certifications such as SnowPro Core or Advanced and Azure Data Engineer Associate - Conversational Spanish for LATAM interaction
- Snowflake development: Builds and tunes Snowflake structures by applying best practices in architecture, performance, and role-based access control. - Semantic models: Builds and optimizes Power BI semantic models with Data Analysis Expressions (DAX) and Power Query, connected to the cloud data warehouse. - Reporting: Develops enterprise-grade reports and migrates existing ones to the new data foundation.
- Hands-on Snowflake development, including architecture, performance tuning, role-based access control, and end-to-end implementations - Proven experience building and optimizing Power BI semantic models, Data Analysis Expressions (DAX), Power Query, and enterprise-grade reports connected to a cloud data warehouse - Hands-on experience with data integration pipelines in production, preferably Azure Data Factory (equivalent experience in other cloud platforms is considered), and familiarity with standardized ingestion frameworks
- Data modeling: Designs dimensional and enterprise data models (star schema, fact and dimension tables, slowly changing dimensions, surrogate keys, data marts) by translating existing views into a structured, high-quality model. - Snowflake development: Builds and tunes Snowflake structures by applying best practices in architecture, performance, and role-based access control. - Semantic models: Builds and optimizes Power BI semantic models with Data Analysis Expressions (DAX) and Power Query, connected to the cloud data warehouse.
- Proven experience designing dimensional and enterprise data models (star schema, fact and dimension tables, slowly changing dimensions, surrogate keys, data marts) - Hands-on Snowflake development, including architecture, performance tuning, role-based access control, and end-to-end implementations - Proven experience building and optimizing Power BI semantic models, Data Analysis Expressions (DAX), Power Query, and enterprise-grade reports connected to a cloud data warehouse
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
Our client is a global leader in the consumer packaged goods (CPG) industry. Its supply chain division is moving reporting to a cloud data warehouse. A first migration kept reports running, and the semantic models now need structure and best practices. This role opens a new engagement and shapes the data foundation that every future report depends on.
The Analytics Developer Senior turns existing data views into a reliable dimensional model and builds the semantic layer that feeds business dashboards. Once the model is stable, the professional evolves current dashboards and proposes new ones. The role combines hands-on development with direct interaction with client management and product leadership.
Data modeling: Designs dimensional and enterprise data models (star schema, fact and dimension tables, slowly changing dimensions, surrogate keys, data marts) by translating existing views into a structured, high-quality model.
Snowflake development: Builds and tunes Snowflake structures by applying best practices in architecture, performance, and role-based access control.
Semantic models: Builds and optimizes Power BI semantic models with Data Analysis Expressions (DAX) and Power Query, connected to the cloud data warehouse.
Reporting: Develops enterprise-grade reports and migrates existing ones to the new data foundation.
Dashboard evolution: Improves current dashboards and proposes new ones by learning supply chain data and business needs.
Data integration: Builds and monitors data integration pipelines with Python and orchestration tools such as Azure Data Factory, using standardized ingestion frameworks.
Business partnership: Gathers requirements, leads workshops, and validates solutions with client management and product leadership by co-creating solutions instead of taking orders.
Agile delivery: Works in agile teams and takes part in team ceremonies to deliver in short cycles.
Fluent English (B2 to C1), verbal and written, for global interaction
Proven experience designing dimensional and enterprise data models (star schema, fact and dimension tables, slowly changing dimensions, surrogate keys, data marts)
Hands-on Snowflake development, including architecture, performance tuning, role-based access control, and end-to-end implementations
Proven experience building and optimizing Power BI semantic models, Data Analysis Expressions (DAX), Power Query, and enterprise-grade reports connected to a cloud data warehouse
Hands-on experience with data integration pipelines in production, preferably Azure Data Factory (equivalent experience in other cloud platforms is considered), and familiarity with standardized ingestion frameworks
Advanced SQL and Python for pipelines and automation
Proven experience working directly with business stakeholders in requirements gathering, workshops, co-creation, and solution validation (not an order-taker profile)
Solid experience in agile teams and their ceremonies
DevOps practices: Git, Azure DevOps, and continuous integration and delivery (CI/CD) for database change promotion
Understanding of SAP data structures and extraction patterns
Experience in the CPG industry, especially with supply chain data
Experience with sell-in, sell-out, and retail or market research data
Certifications such as SnowPro Core or Advanced and Azure Data Engineer Associate
Conversational Spanish for LATAM interaction
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