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- Tasks: Join a dynamic team to design and develop cloud data solutions using AWS.
- Company: Leading tech firm focused on innovative data and analytics solutions.
- Benefits: Competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Agile team culture with excellent career advancement potential.
- Why this job: Make a real impact by transforming data systems in a collaborative environment.
- Qualifications: Experience with AWS tools, Python programming, and strong data engineering skills.
The predicted salary is between 40000 - 50000 £ per year.
The role falls within the Data Contract Delivery Area of the client's contract. The group provides a wide range of data and analytics solutions in support of our client's business priorities: maximise revenues, bear down on fraud, and cloud migration. This role involves migrating data from legacy on-premise systems (primarily Oracle and Informatica) to a new AWS cloud-native architecture. You will be part of an Agile software delivery team working closely with other engineers and supported by project managers, business analysts and architects, with additional client and key stakeholder interaction as required.
We are looking for strong AWS Senior Data Engineers who can design and deliver cloud transformation projects. Your work will be to:
- Support the technical lead with design and client interactions, and support junior engineers with their development.
- Design, develop and test data pipelines: create robust pipelines to ingest, process, and transform data, ensuring it is ready for analytics and reporting.
- Implement ETL/ELT processes: develop and test extract, transform, load (ETL) or extract, load, transform (ELT) workflows to seamlessly move data from source systems to data warehouses/data lakes/lake houses using open source and AWS tools.
- Adopt DevOps practices: utilize devops methodologies and tools for continuous integration and deployment (CI/CD).
Must-have skills:
- Proficiency with core AWS tools (AWS Glue, Lambda, S3, Redshift)
- Programming skills (Python)
- SQL and data storage technologies: knowledge of data warehouses, database technologies, and technologies (AWS Redshift, AWS RDS)
- AWS data lakes: experience with AWS S3 for storing and processing structured and unstructured data sets.
Nice-to-have skills:
- Knowledge of open table formats (Iceberg/Delta)
- AWS tools: experience with Amazon CloudWatch, SNS, Athena, DynamoDB, EMR, Kinesis
- Data modelling
- Job scheduling/orchestration
- Data virtualisation tools (Denodo)
- ALM tooling (Jira, Confluence)
- CI/CD toolsets (GitLab, Terraform)
- Reporting tools (Business Objects, Power BI, Pentaho BA)
- Data analytics toolset (SAS Viya)
- Observability tools (Grafana, Dynatrace)
Experience:
You should have experience as a senior data engineer delivering within large scale data analytics solutions and the ability to operate at all stages of the software engineering lifecycle, as well as some experience in the following:
- Awareness of devops culture and modern engineering practices
- Experience of agile scrum based delivery
- Proactive in nature, personal drive, enthusiasm, willingness to learn
- Excellent communications skills including stakeholder management
- Developing solutions within the given architecture and adhering to specified NFRs
- Supporting other engineers within your team
- Continually looking for ways to improve
Senior AWS Data engineer (LDW Data Warehouse Discovery) employer: Experis
Contact Detail:
Experis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AWS Data engineer (LDW Data Warehouse Discovery)
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Don’t just tell them what you can do; show them! Create a portfolio of your projects, especially those involving AWS tools like Glue or Redshift. This will give potential employers a clear view of your capabilities and how you can contribute to their team.
✨Ace the Interview
Prepare for your interviews by practicing common questions related to AWS and data engineering. Be ready to discuss your past experiences and how they relate to the role. Remember, it’s not just about technical skills; your communication and teamwork abilities matter too!
✨Apply Through Our Website
We’ve got some fantastic roles listed on our website, so make sure to check them out! Applying directly through us not only shows your interest but also gives you a better chance of getting noticed by our hiring team.
We think you need these skills to ace Senior AWS Data engineer (LDW Data Warehouse Discovery)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior AWS Data Engineer role. Highlight your experience with AWS tools, data pipelines, and any cloud transformation projects you've worked on. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific examples of projects where you've designed and developed ETL/ELT processes or worked with AWS data lakes. This helps us understand your hands-on experience and how you can contribute to our team.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for key achievements and avoid jargon unless it's relevant. We appreciate straightforward communication that gets to the heart of your experience.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Experis
✨Know Your AWS Tools Inside Out
Make sure you’re well-versed in core AWS tools like Glue, Lambda, S3, and Redshift. Be prepared to discuss how you've used these tools in past projects, especially in relation to data migration and cloud transformation.
✨Showcase Your ETL/ELT Expertise
Be ready to explain your experience with ETL and ELT processes. Bring examples of data pipelines you've designed and the challenges you faced, as well as how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Emphasise Your Agile Experience
Since this role involves working in an Agile environment, highlight your experience with Agile methodologies. Share specific instances where you contributed to a team’s success through collaboration and adaptability.
✨Communicate Clearly and Confidently
Strong communication skills are key, especially when interacting with stakeholders. Practice articulating your thoughts clearly and concisely, and be prepared to discuss how you’ve managed stakeholder expectations in previous roles.