At a Glance
- Tasks: Design and maintain large-scale data pipelines and ETL workflows for enterprise datasets.
- Company: Join a leading tech firm in Sheffield, UK, focused on innovative data solutions.
- Benefits: Competitive pay at £65 per hour, with opportunities for professional growth.
- Other info: Dynamic work environment with a focus on collaboration and operational excellence.
- Why this job: Make an impact by optimising cloud-based data infrastructure and enhancing real-time analytics.
- Qualifications: Experience in data engineering, strong scripting skills, and knowledge of Azure platforms required.
The predicted salary is between 54000 - 66000 £ per year.
- Design build and maintain largescale data pipelines and ETL workflows across enterprise datasets
- Ingest provision and manage raw enriched and curated data assets for analytics platforms
- Improve reliability scalability and realtime data ingestion capabilities
- Support and enhance cloudbased data ingestion infrastructure and platform services
- Acquire transport clean transform and integrate data from internal and external sources
- Perform exploratory data analysis and onboard new data sources
- Develop automated data engineering workflows and optimize data processing pipelines
- Manage data modelling data warehousing data integration and data cataloguing activities
- Support realtime analytics and streaming data platforms
- Contribute to cloud infrastructure engineering platform operations and production support
- Implement cloud cost optimization and platform efficiency improvements
- Collaborate with engineering analytics infrastructure and cybersecurity teams
- Support Dev Ops automation monitoring and operational excellence initiatives
- Maintain documentation governance standards and operational procedures
- Role Description
- Role Senior Data Engineer
- Sheffield, UK
- 6 Months contract
Responsibilities
- Design build and maintain largescale data pipelines and ETL workflows across enterprise datasets
- Ingest provision and manage raw enriched and curated data assets for analytics platforms
- Improve reliability scalability and realtime data ingestion capabilities
- Support and enhance cloudbased data ingestion infrastructure and platform services
- Acquire transport clean transform and integrate data from internal and external sources
- Perform exploratory data analysis and onboard new data sources
- Develop automated data engineering workflows and optimize data processing pipelines
- Manage data modelling data warehousing data integration and data cataloguing activities
- Support realtime analytics and streaming data platforms
- Contribute to cloud infrastructure engineering platform operations and production support
- Implement cloud cost optimization and platform efficiency improvements
- Collaborate with engineering analytics infrastructure and cybersecurity teams
- Support Dev Ops automation monitoring and operational excellence initiatives
- Maintain documentation governance standards and operational procedures
- To be successful in this role you should have
- Experience with SRE principles and Azure Dev Ops
- Strong scripting skills using Bash Power Shell and Azure CLI
- Programming experience with Python C Java and objectoriented development
- Strong SQL and Kusto Query Language KQL experience
- Experience with Git Hub source control systems and CICD pipelines
- Strong Linux administration and scripting experience
- Knowledge of networking operating systems storage technologies and infrastructure fundamentals
- Experience in Data Acquisition and Cloud Based Data Pipelines
- Experience with Data Transport Data Cleaning and Data Integration
- Strong Data Engineering pipeline automation productionization and optimization skills
- Experience designing and maintaining ETL workflows and largescale data pipelines
- Knowledge of Data Warehousing Data Modeling and Data Cataloguing
- Experience with Real Time Analytics and Streaming Data Platforms
- Cloud Cost Optimization experience
- Strong Azure platform knowledge including Azure AD Azure IAM Networking Compute Storage Databases and Containers
- Experience with Azure Data Factory Azure Databricks Unity Catalog Azure Functions Azure Logic Apps Azure Monitor Azure Log Analytics Azure Data Lake Synapse Analytics and Power BI
- Experience with Kubernetes and Cloud Native platforms
- Knowledge of Nginx Apache Cosmos DB Linux Prometheus Grafana and Elasticsearch
- Experience with Infrastructure as Code tools such as Terraform ARM Chef and Ansible
- Experience with Azure Event Hubs Kafka and Spark Streaming
- Exposure to SIEM and SOAR platforms is advantageous
- Experience working in highly regulated enterprise environments is preferred
- #J-18808-Ljbffr
Senior Data Engineer in Sheffield employer: LTM
LTM is an excellent employer that fosters a collaborative and innovative work culture in Bradford, UK. With a strong emphasis on employee growth, we offer continuous professional development opportunities and support for career advancement, making it a rewarding place for those looking to make a meaningful impact in capital projects. Our commitment to work-life balance and a supportive team environment ensures that every employee feels valued and empowered to succeed.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in Sheffield
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like LTM before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like LTM.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like LTM.
We think you need these skills to ace Senior Data Engineer in Sheffield
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at LTM, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to LTM, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab LTM’s attention and show the tangible impact of your work.
How to prepare for a job interview at LTM
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at LTM.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at LTM.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at LTM.
