Data Engineer – Databricks

Jobtailor; São Paulo; Presencial; BRL 180 000 - 280 000; Tempo integral

Resumo da oferta

Jobtailor is seeking a senior Data Engineer to design and implement scalable data pipelines in Google Cloud Platform, building Data Lake, Data Warehouse and Data Mart solutions. You will translate business requirements into robust data models and ensure semantic quality for BI consumption.

You will collaborate with cross-functional teams, apply governance standards, optimize costs and advance best practices in data architecture, including Data Mesh and Lakehouse patterns.

Qualificações

• Advanced experience in conceptual, logical and physical data modeling for analytics.

Responsabilidades

• Design and implement scalable data pipelines in GCP.
• Define data models with emphasis on performance, scalability and usability.
• Support data consumption through BI tools, ensuring semantic quality and query performance.
• Ensure data governance, security and compliance throughout the data lifecycle.

Conhecimentos

Data Modeling

SQL

BigQuery

Python

Spark

GCP

Power BI

CI/CD

Data Mesh

Lakehouse

Streaming

Star Schema

Snowflake

Data Vault

Data Pipeline Design

Ferramentas

Google Cloud Platform

Power BI

Dataflow

Dataproc

Pub/Sub

Cloud Storage

Composer

CI/CD Tools

Descrição da oferta de emprego

• Design and implement efficient, scalable data pipelines aligned with business needs.
• Develop and maintain data ingestion and transformation pipelines in Google Cloud Platform (GCP) environments.
• Build solutions for Data Lake, Data Warehouse and Data Mart.
• Define and apply relational and dimensional data modeling standards with a focus on performance, scalability and usability.
• Translate business requirements into clear, consistent and sustainable data models.
• Support data consumption through Business Intelligence tools, ensuring semantic quality and query performance.
• Ensure data quality, governance, security and compliance throughout the data lifecycle.
• Monitor and optimize cloud environment costs and performance.
• Collaborate with multidisciplinary teams to promote data engineering and architecture best practices.

Requirements

• Advanced experience in conceptual, logical and physical data modeling, especially in analytical environments.
• Strong SQL skills and best practices for Data Warehouse design and BigQuery.
• Experience with Python and Spark for data processing.
• Proficiency in the GCP ecosystem, including BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage and Composer.
• Experience with data visualization tools, especially Power BI, including semantic modeling, performance and data consumption.
• Familiarity with CI/CD practices, code versioning and pipeline automation.
• Knowledge of modern data architectures such as Data Mesh, Lakehouse and streaming solutions.
• Experience with different data modeling approaches such as Star Schema, Snowflake and Data Vault.
• Experience in scalable, governance-oriented data environments.

Core Competencies

Demonstrates expertise in designing and implementing scalable data pipelines and data modeling standards within GCP environments, ensuring data quality, governance, and compliance. Proficient in utilizing advanced data processing tools and techniques to support business intelligence and data consumption needs.

Highest-signal resume keywords

• Data Modeling
• SQL Skills
• GCP Proficiency
• Python and Spark Experience
• Data Visualization with Power BI

ATS Optimization Keywords

Hard Skills

• Data Pipeline Design
• Relational and Dimensional Data Modeling
• BigQuery
• Dataflow
• Dataproc
• Pub/Sub
• Cloud Storage
• Composer
• Data Governance
• Data Quality Assurance

Soft Skills

• Collaboration
• Communication

Industry Keywords

• Data Lake
• Data Warehouse
• Data Mart
• Data Mesh
• Lakehouse
• Streaming Solutions
• Star Schema
• Snowflake
• Data Vault

Tools & Technologies

• Google Cloud Platform
• Power BI
• CI/CD Practices
• Data Visualization Tools