At a Glance
- Tasks: Design and build scalable data platforms using cutting-edge cloud technologies.
- Company: Join a leading tech firm focused on digital transformation and innovation.
- Benefits: Flexible working, extensive training opportunities, and a positive work-life balance.
- Other info: Dynamic team environment with opportunities for career growth and development.
- Why this job: Make an impact by leveraging AI and big data in exciting projects.
- Qualifications: Experience in data engineering and proficiency in cloud platforms like AWS and Azure.
The predicted salary is between 60000 - 80000 € per year.
The Data Platforms team is part of the Insights and Data Global Practice and has seen strong growth and continued success across a variety of projects and sectors. Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers' digital and data transformation journey using the modern cloud platforms. We specialise in using the latest frameworks, reference architectures and technologies using AWS, Azure and GCP along with various data platforms like Databricks, Snowflake, Quantexa, Palantir, SAS.
As a Data Engineer, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations.
What You Will Bring
- Design and build high-performance data pipelines: to extract, transform, and load data into Cloud Data Lake Storage and other Cloud services.
- Develop and maintain secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data.
- Implement ETL/ELT Processes: Develop Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) workflows to seamlessly move data from source systems to Data Warehouses, Data Lakes, and Lake Houses using Open Source and cloud tools.
- Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leveraging ML to develop predictive models and drive business insights.
- Monitor and optimize data pipelines and infrastructure: Analyze performance metrics, identify bottlenecks, and implement optimizations for efficiency and scalability.
- Collaborate with cross-functional teams: Work closely with business analysts, data scientists, and DevOps engineers to ensure successful data platform implementations.
- Stay ahead of the curve: Continuously learn and adapt to the evolving landscape of big data technologies and best practices with a focus on how AI can support you in your delivery work.
Minimum 10+ years of experience as a Data Engineer or similar role. Proven expertise in the technologies below, and data pipeline development and strong understanding of data warehousing concepts and practices. Excellent problem-solving and analytical skills and strong communication and teamwork skills.
In addition to these core skills, you should have specialist experience in one or more of the following technologies:
- Azure Databricks: Design and build high-performance data pipelines: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Experience of Databricks ML and Azure ML to develop predictive models and drive business insights.
- AWS Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR, Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions.
- Programming Skills: Strong experience with modern programming languages such as Python, Java, Scala.
It will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
What we’ll offer you
You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means we embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements. You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more.
Data Engineer employer: Ontologize LLC
At Capgemini, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters innovation and collaboration. As a Data Engineer, you will enjoy a hybrid-first working model that promotes a healthy work-life balance, alongside extensive training and development opportunities to enhance your skills in cutting-edge technologies. With access to a wealth of resources and a supportive team environment, you'll be empowered to drive impactful data transformations while advancing your career in vibrant locations like Manchester, London, Bristol, Newcastle, and Birmingham.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, attend meetups, and join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AWS, Azure, or GCP. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data pipelines, cloud platforms, and any relevant technologies like Databricks or AWS. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Be sure to mention specific projects or experiences that relate to the job description.
Showcase Your Problem-Solving Skills:In your application, don’t forget to highlight your problem-solving abilities. Share examples of challenges you've faced in previous roles and how you overcame them, especially in relation to data warehousing or pipeline development.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at Ontologize LLC
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Azure Databricks and AWS tools. Brush up on your knowledge of data pipelines, ETL/ELT processes, and cloud services to show you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Use examples that highlight your analytical skills and ability to optimise data pipelines or troubleshoot issues effectively.
✨Collaborate Like a Pro
Since teamwork is key in this role, be ready to share experiences where you’ve worked with cross-functional teams. Highlight how you’ve collaborated with data scientists or business analysts to achieve successful outcomes.
✨Stay Ahead of the Curve
Demonstrate your commitment to continuous learning by discussing recent trends in big data technologies or AI/ML models. Mention any courses or certifications you’ve pursued to keep your skills sharp and relevant.
