Data Engineer designing and building production data pipelines for AI and ML workloads at Capgemini Engineering. Focus on end to end data lifecycle management and AWS infrastructure.
About the role
- Senior Data Engineer delivering high-quality data solutions at a leading Google Cloud consultancy. Designing, building, and maintaining scalable data pipelines and infrastructure for complex data analysis.
Responsibilities
- How You’ll Shape Our SuccessThe purpose of this role is to design, build, and maintain scalable data pipelines and infrastructure that enable the efficient processing and analysis of large, complex data sets.
- What You’ll DoDevelop and maintain automated data processing pipelines using Google Cloud:
- Design, build, and maintain data pipelines to support data ingestion, ETL, and storage
- Build and maintain automated data pipelines to monitor data quality and troubleshoot issues
- Implement and maintain databases and data storage solutions:
- Stay up-to-date with emerging trends and technologies in big data and data engineering
- Ensure data quality, accuracy, and completeness
- Implement and enforce data governance policies and procedures to ensure data quality and accuracy:
- Collaborate with data scientists and analysts to design and optimise data models for analytical and reporting purposes
- Develop and maintain data models to support analytics and reporting
- Monitor and maintain data infrastructure to ensure availability and performance
Requirements
- What You’ll Need to Succeed
- Experience in contributing to technical decision making during in-flight projects.
- A track record of being involved in a wide range of projects with various tools and technologies, and solving a broad range of problems using your technical skills.
- Demonstrable experience of utilising strong communication and stakeholder management skills when engaging with customers
- Significant experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
- Strong proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL, or Oracle.
- Experience with big data technologies such as Hadoop, Spark, or Hive.
- Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow.
- Proficiency in Python and at least one other programming language such as Java, or Scala.
- Willingness to mentor more junior members of the team.
- Strong analytical and problem-solving skills with the ability to work independently and in a team environment.
Benefits
- **Financial:**
- Competitive base salary.
- Discretionary company bonus scheme.
- Employee referral scheme
- Meal Vouchers
- **Health & Wellbeing:**
- Health Care Package
- Life and Health Insurance
- Bookster
- **Time Off & Flexibility: **
- 28 days of annual leave
- Floating bank holidays
- An extra paid day off on your birthday.
- Ten paid learning days per year.
- Flexible working hours
- Sabbatical leave (after 5 years).
- Work from anywhere (up to 3 weeks per year).
- **Development & Recognition: **
- Industry-recognised training & certifications.
- Bonusly: employee recognition and rewards platform.
- Clear opportunities for career development.
- Length of Service Awards.
- **Extra Perks:**
- Regular company events.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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