FBS Analytics Engineer

Overview

Analytics Engineer role within the Service Analytics and AI organization, designing, building and maintaining scalable data pipelines and analytics solutions that support Advanced Analytics, Business Intelligence and Data Science initiatives.

What you'll do

• Lead the design, development and deployment of scalable and robust data pipelines, ensuring seamless data integration and processing across diverse systems.
• Establish and uphold best practices for data engineering, including coding standards, data governance, performance optimization and automation strategies.
• Participate in code reviews, provide constructive feedback, and contribute to the team's continuous improvement in coding practices and methodologies.
• Design, build and maintain robust ETL/ELT pipelines, reusable frameworks and libraries to process and transform data from diverse sources, ensuring accuracy, quality and consistency.
• Implement CI/CD pipelines to streamline the deployment, testing and maintenance of analytics engineering processes.
• Partner with data scientists, engineers, analysts, product managers and business stakeholders to understand requirements.
• Articulate complex technical concepts to non-technical stakeholders, fostering alignment and a shared understanding of data initiatives across teams.
• Perform advanced SQL development, query optimization, complex transformations and large-scale data processing.
• Design and develop enterprise-scale data solutions using Snowflake, including performance tuning, data sharing, tasks, streams and modern platform capabilities.
• Build scalable transformation frameworks, reusable business logic, testing, documentation and deployment pipelines using dbt.
• Model star schemas, conformed dimensions, historical tracking, KPI frameworks and analytical data models.
• Manage data quality, lineage, metadata, testing, observability and model lifecycle.
• Deliver data products within Agile product teams and modern cloud environments.

What you'll need

• 3+ years of experience working as an Analytics Engineer or equivalent.
• Hands-on experience with SQL, SQL Server, Python, Snowflake and dbt.
• Experience in version control systems such as Git, and workflow management tools such as Airflow.
• Proven experience in designing and building scalable data pipelines.
• Expertise in ETL/ELT processes, data modeling and integration of data from multiple sources into a data warehouse.
• Experience with CI/CD workflows and tools for data engineering.
• Strong problem-solving and analytical skills, with the ability to work effectively in a collaborative environment.

Details

• Location: Brazil.
• Flexible work arrangements (remote and/or office-based).
• Capgemini acts as Employer of Record, managing local payroll and benefits.