At a Glance
- Tasks: Design and maintain scalable data pipelines for impactful analytics and machine learning.
- Company: Join a forward-thinking tech company focused on data-driven solutions.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and career advancement.
- Why this job: Be at the forefront of data engineering and shape the future of analytics.
- Qualifications: Strong SQL skills and experience with Python or Java required.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a highly skilled Senior Data Engineer to design, build, and maintain scalable data pipelines and architectures. You will play a key role in enabling data-driven decision-making by ensuring data is reliable, accessible, and optimized for analytics and machine learning use cases.
Data Engineering & Architecture
- Design, develop, and maintain scalable ETL/ELT pipelines
- Build and optimize data warehouses, data lakes, and lakehouse architectures
- Ensure efficient data ingestion, transformation, and storage
- Develop reusable frameworks and standards for data engineering best practice
Data Modelling & Warehousing
- Design data models (dimensional, normalized, star/snowflake schemas)
- Collaborate with analytics teams to support BI and reporting requirements
- Optimize data structures for performance and scalability
Cloud & Platform Engineering
- Build and maintain data solutions on cloud platforms (Azure, AWS, GCP)
- Implement and manage data tools such as:
- Azure Data Factory / Synapse / Databricks
- AWS Glue / Redshift / EMR
- Google BigQuery / Dataflow
- Ensure systems are secure, scalable, and cost-efficient
Data Pipeline & Workflow Management
- Develop orchestration workflows (e.g., Airflow, Prefect, Azure Data Factory)
- Monitor and troubleshoot pipelines to ensure high availability and performance
- Implement robust error handling, logging, and alerting
Data Quality & Governance
- Ensure data quality, integrity, and consistency
- Implement validation, testing, and monitoring frameworks
- Work with governance teams on data security, compliance, and policies
Collaboration & Leadership
- Partner with Data Scientists, Analysts, and Product teams
- Mentor junior data engineers and promote best practices
- Contribute to architectural decisions and strategic planning
Technical Skills
- Strong proficiency in SQL and data modelling
- Excellent programming skills in Python, Scala, or Java
- Hands-on experience with distributed data frameworks (Spark, Hadoop)
- Experience with data pipelines and ETL tools
- Expertise in at least one cloud platform: Azure (Synapse, Data Factory, Databricks), AWS (S3, Glue, Redshift, Lambda), GCP (BigQuery, Dataflow)
Data Platform Expertise
- Experience with data warehousing solutions
- Streaming technologies (Kafka, Kinesis, Pub/Sub)
- Familiarity with DevOps/DataOps practices
- CI/CD pipelines
- Infrastructure as Code (Terraform, ARM, CloudFormation)
Senior Data Engineer employer: NTT DATA
As a Senior Data Engineer at our company, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. We offer competitive benefits, including flexible working arrangements and opportunities for professional development, all set in a vibrant location that fosters creativity and growth. Join us to be part of a forward-thinking team dedicated to leveraging data for impactful decision-making.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to a hiring manager.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ETL pipelines or cloud solutions. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with SQL, Python, and cloud platforms like AWS or Azure. Practice common data engineering scenarios to demonstrate your problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic roles waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with data pipelines, cloud platforms, and any relevant programming skills. We want to see how your background aligns with what we're looking for!
Showcase Your Projects:Include specific projects that demonstrate your expertise in building scalable data architectures and ETL/ELT pipelines. We love seeing real-world examples of your work, so don’t hold back on the details!
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. We appreciate a personal touch, so let your personality come through.
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’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at NTT DATA
✨Know Your Data Engineering Fundamentals
Brush up on your data engineering concepts, especially around ETL/ELT pipelines and data modelling. Be ready to discuss your experience with different architectures like data lakes and warehouses, as well as the specific tools mentioned in the job description.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency in SQL and programming languages like Python or Scala. You might be asked to solve a problem on the spot, so practice coding challenges related to data manipulation and pipeline creation.
✨Familiarise Yourself with Cloud Platforms
Since the role involves working with cloud solutions, make sure you understand the specifics of Azure, AWS, or GCP. Be ready to discuss how you've implemented data solutions on these platforms and any relevant tools you've used.
✨Emphasise Collaboration and Leadership
This position requires working closely with various teams, so highlight your experience in collaboration and mentoring. Share examples of how you've partnered with data scientists or analysts and contributed to team success.
