# Data Engineer

**Company**: Service Analytics and AI organisation
**Location**: London
**Work arrangement**: onsite
**Experience**: mid
**Job type**: full-time
**Category**: Engineering
**Industry**: Finance

**Apply**: https://jobs.workable.com/view/8mfJSQRsDFPj11qWGHRR3S/hybrid-analytics-engineer%2C-service-ops-analytics-%26-ai-in-new-york-at-capgemini?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_67f442ae-838

## Description

The goal of this role is to build curated data products leveraging data from structured and unstructured enterprise data sources to enable business intelligence, data science, and advanced analytics. The successful candidate will play a crucial role in designing, building, and maintaining scalable data pipelines and analytics solutions that empower Advanced Analytics, Business Intelligence, and Data Science initiatives.

Key Responsibilities:

- Design, develop, and deploy 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 optimisation, 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.

Qualifications:

- Hands-on experience with SQL, Python, dbt, and Snowflake.

- Experience in version control systems such as Git, and workflow management tools such as Airflow.

- Proven experience in designing and building scalable data pipelines, and architectures.

- Strong understanding of data governance, quality assurance, and performance optimisation in a data engineering context.

- Expertise in ETL/ELT processes, data modelling, 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.

## Skills

### Required
- SQL
- Python
- dbt
- Snowflake
- Git
- Airflow

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Source: [Apply at jobs.workable.com](https://jobs.workable.com/view/8mfJSQRsDFPj11qWGHRR3S/hybrid-analytics-engineer%2C-service-ops-analytics-%26-ai-in-new-york-at-capgemini?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)