Senior Data Engineer – Databricks, Unity Catalog

Stefanini Brasil

. Develop, optimize, and maintain data transformation pipelines using dbt Core and Databricks (Unity Catalog, Delta Lake, Spark SQL) .

Posted 10/22/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing data transformation pipelines using dbt Core and Databricks, with a strong focus on data quality, governance, and dimensional modeling for BI tools. Proficient in version control and scripting with Git and Python, ensuring efficient automation and orchestration.

Highest-signal resume keywords

Advanced SQL ProficiencyDbt Core in ProductionDatabricks ExperienceData Modeling ExpertiseVersion Control & Scripting

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Advanced SQLDbt CoreDimensional ModelingData Quality AssuranceData Transformation PipelinesPython ScriptingGit WorkflowsCI/CD ConceptsSpark SQLSlowly Changing Dimensions

Tools & Technologies

DatabricksUnity CatalogDelta LakePower BIGitLabApache AirflowAWS MWAACosmos Library

Industry Keywords

Data EngineeringSAP ECCPM ModulesCO ModulesBODS PipelinesAWS ArchitectureLakehouse Federation

Tech Stack

Tools & technologies

AirflowApacheAWSPythonSparkSQLUnity

About the role

Key responsibilities & impact

Develop, optimize, and maintain data transformation pipelines using dbt Core and Databricks (Unity Catalog, Delta Lake, Spark SQL)
Apply dimensional modeling (Star Schema) for efficient consumption in BI tools
Ensure data quality and governance by writing generic and singular tests in dbt and performing rigorous source-to-target validations
Work independently from business rules specifications, identifying inconsistencies and proposing efficient technical solutions
Version code and pipelines using Git workflows, Merge Requests, and CI/CD concepts via GitLab
Create and maintain supporting Python scripts and assist with understanding orchestration DAGs

Requirements

What you’ll need

Advanced SQL: Proficiency in CTEs, window functions, deduplication techniques, data handling (dates/numbers), and support for Slowly Changing Dimensions (SCD Type 2)
dbt Core in Production: Hands-on experience with models, sources, tests, seeds, snapshots, Jinja macros, materializations (ephemeral, incremental), contracts, and use of the ref/var functions
Databricks: Experience with Unity Catalog, Delta Lake, SQL Warehouse, and Spark SQL
Data Modeling: Experience with dimensional modeling (Star Schema) focused on high performance in Power BI
Version Control & Scripting: Proficiency in Git, Merge Request workflows, familiarity with CI/CD in GitLab, and functional Python skills for automation and DAG reading
Technical English at a minimum B2 level for reading and writing technical documentation
Preferred: 5 or more years of prior experience in Data Engineering
Preferred: Experience with orchestration using Apache Airflow, especially AWS MWAA, and the Cosmos library for dbt execution
Preferred: Knowledge of SAP ECC data, PM and CO modules, or BODS pipelines
Preferred: Knowledge of AWS architecture (S3) and Lakehouse Federation

Benefits

Comp & perks

Meal allowance or meal voucher
Discounts on courses, universities, and language institutions
Stefanini Academy — a platform offering free, up-to-date online courses with certificates
Mentoring
Benefits club for consultations and medical exams
Health insurance
Dental insurance
Benefits and discounts at leading establishments
Travel club
Pet insurance partnership