FBS Senior Analytics Engineer

Overview

Senior Analytics Engineer on the Analytics Engineering team 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.
• Proactively monitor and troubleshoot data pipelines, ensuring high availability, reliability and performance across all data engineering workflows.
• 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, translate them into actionable technical specifications and deliver impactful data solutions.
• Articulate complex technical concepts to non-technical stakeholders, fostering alignment and a shared understanding of data initiatives across teams.
• Build a semantic data layer, define and implement data products, and deliver AI-driven solutions that fuel business growth and enhance customer experience.

What you'll need

• 5+ years of experience working as an Analytics Engineer or equivalent.
• Hands-on experience with SQL, SQL Server, Python, DBT and Snowflake.
• Advanced SQL development, query optimization, complex transformations and large-scale data processing.
• Enterprise-scale data solutions using Snowflake, including performance tuning, data sharing, tasks, streams and modern platform capabilities.
• Scalable transformation frameworks, reusable business logic, testing, documentation and deployment pipelines using dbt.
• Experience in version control systems such as Git, and workflow management tools such as Airflow.
• Proven experience designing and building scalable data pipelines and architectures.
• Star schemas, conformed dimensions, historical tracking, KPI frameworks and analytical data models.
• Strong understanding of data governance, quality assurance and performance optimization in a data engineering context.
• Data quality, lineage, metadata management, testing, observability and model lifecycle management.
• 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.
• Experience delivering data products within Agile product teams and modern cloud environments.
• Strong problem-solving and analytical skills, with the ability to work effectively in a collaborative environment.

Details

• Employment is through Capgemini as Employer of Record, which manages local payroll and benefits.
• Flexible work arrangements (remote and/or office-based).
• Competitive salary and performance-based bonuses, with a comprehensive benefits package including private health insurance and paid time off.
• Training and development opportunities in partnership with renowned companies.