Mid-Senior Data Modeller

• Develop conceptual, logical, and physical data models for Azure Synapse warehouse and data mart environments.
• Design dimensional models: defining grain, building fact and dimension structures, and handling surrogate keys and slowly changing dimensions.
• Make normalization and denormalization decisions based on how the data will actually be queried.
• Profile client source systems to understand content, quality, and relationships before modelling against them.
• Produce source-to-target mapping documentation detailed enough for engineering to build from without guesswork.
• Analyze existing ETL and SSIS logic during Synapse migrations to recover embedded business rules, and design the target model that replaces them.
• Catalogue data assets and build out metadata repositories.
• Partner with architects, technical leads, and business teams to translate business questions into structures that answer them., * Completed background checks will be required before the start date if you are selected as a winning candidate.
• As a winning candidate, you will be required to disclose your engagement with DevEngine as a primary client on your professional LinkedIn profile.

This is a long-term contract opportunity without an end date. The engagement is fully remote, and the successful candidate can be located anywhere in Latin America. You’ll need strong English communication skills (B2+ or higher) for this role., * 4+ years in a data modelling or warehouse design role, with models you’ve taken from requirements through to production.

• Strong dimensional modelling skills - star and snowflake schemas, grain definition, surrogate keys, and slowly changing dimensions.
• Demonstrated ability to work across conceptual, logical, and physical layers, and to explain why a model is shaped the way it is.
• Hands-on experience modelling for Microsoft Azure Data & Analytics, particularly Azure Synapse, with working familiarity with Azure Data Factory and Azure Data Lake Storage.
• Strong SQL, including complex queries, and solid working experience with T-SQL and SQL Server.
• Experience profiling unfamiliar source systems and reverse-engineering business rules out of existing ETL or SSIS logic.
• Database performance tuning experience, with a clear understanding of how modelling decisions drive query performance.
• Proven data warehouse and data mart experience.
• Strong knowledge of data structures and the ability to extract data from a range of source systems (such as Cognos, Informatica, Hyperion, and similar).

Nice-to-Have:

• Experience delivering models at enterprise scale, where design decisions affect multiple teams and systems.
• Manufacturing industry experience.
• Hands-on use of dedicated modelling tools such as ERwin, ER/Studio, or SqlDBM.
• Consulting or client-facing experience.
• Familiarity with Data Vault or other modelling methodologies.
• Relevant Microsoft Azure data certifications.
• Exposure to Informatica PowerCenter.
• PL/SQL experience - the core stack is SQL Server and T-SQL, so this is a bonus.