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- Tasks: Design and maintain scalable data pipelines and optimise AWS-based infrastructure for GenAI applications.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on collaboration and career advancement.
- Why this job: Be part of a team that shapes the future of AI with cutting-edge technology.
- Qualifications: Strong experience in PySpark, SQL, Python, and AWS services required.
The predicted salary is between 70000 - 90000 £ per year.
Your responsibilities:
- Design and maintain scalable data pipelines using PySpark, Python, and distributed computing frameworks to support high-volume data processing.
- Architect and optimize AWS-based data and AI infrastructure, ensuring secure, performant, and cost-efficient ingestion, transformation, and storage.
- Develop, finetune, benchmark, and evaluate GenAI/LLM models, including custom training and inference optimization.
- Implement and maintain RAG pipelines, vector databases, and document-processing workflows for enterprise GenAI applications.
- Build reusable frameworks for prompt management, evaluation, and GenAI operations.
- Collaborate with cross-functional teams to integrate GenAI capabilities into production systems and ensure high-quality data, governance, and operational reliability.
Your Profile
Essential skills/knowledge/experience:
- Strong experience with PySpark, distributed data processing, and large-scale ETL/ELT pipelines.
- Strong SQL expertise including star/snowflake schema design, indexing strategies, writing optimized queries, and implementing CDC, SCD Type 1/2/3 patterns for reliable data warehousing.
- Advanced proficiency in Python for data engineering, automation, and ML/GenAI integration.
- Hands-on expertise with AWS services (S3, Glue, Lambda, EMR, Bedrock / custom model hosting).
- Practical experience with GenAI/LLM model creation, finetuning, benchmarking, and evaluation.
- Solid understanding of RAG architectures, embeddings, vector stores, and LLM evaluation methods.
- Experience working with structured and unstructured datasets (documents, logs, text, images).
- Familiarity with scalable data storage solutions (Delta Lake, Parquet, Redshift, DynamoDB).
- Understanding model optimization techniques (quantization, distillation, inference optimization).
- Strong capability to debug, tune, and optimize distributed systems and AI pipelines.
Desirable skills/knowledge/experience:
- Pyspark, Python, SQL, AWS, GenAI
Senior Engineer, Data Engineering employer: Webologix Ltd/ INC
Contact Detail:
Webologix Ltd/ INC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Engineer, Data Engineering
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving PySpark and AWS. We love seeing real-world applications of your expertise, so make sure to highlight your best work.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to data engineering and GenAI. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨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, we’re always on the lookout for talented individuals like you!
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PySpark, AWS, and data engineering. We want to see how your skills match the role, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about GenAI and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool data pipelines or GenAI models, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions of your work.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Webologix Ltd/ INC
✨Know Your Tech Inside Out
Make sure you brush up on your PySpark, Python, and AWS skills. Be ready to discuss specific projects where you've designed scalable data pipelines or optimised cloud infrastructure. The more detailed examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced in data engineering, especially with large-scale ETL/ELT processes. Think of a couple of scenarios where you had to debug or optimise a system, and explain how you approached the problem and what the outcome was.
✨Familiarise Yourself with GenAI Concepts
Since this role involves working with GenAI models, make sure you understand the basics of model creation, finetuning, and evaluation. Be ready to discuss any hands-on experience you have with LLMs and how you've integrated them into production systems.
✨Collaboration is Key
This position requires working with cross-functional teams, so be prepared to share examples of how you've successfully collaborated with others. Highlight your communication skills and how you ensure high-quality data governance and operational reliability in your projects.