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- Tasks: Join us as a Data Engineering Consultant, working with cutting-edge technologies to model and store data.
- Company: Endava is a leading tech company transforming businesses through innovative solutions.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team that values creativity and collaboration while making a real impact.
- Qualifications: We're looking for skills in Python, SQL, and experience with big data tools like Apache Spark.
- Other info: This role is based in London, offering a vibrant work culture and exciting projects.
The predicted salary is between 48000 - 72000 £ per year.
Modelling & Storage: Relational (PostgreSQL, SQL Server), NoSQL (MongoDB, Cassandra), Dimensional modelling.
DevOps & Automation: Docker, Kubernetes, Terraform, CI/CD pipelines for data flows.
Architectural Competencies: Data Modelling: Designing dimensional, relational, and document data lineage and recommend improvements for data ownership and stewardship.
Qualifications:
- Programming: Python, SQL, Scala, Java.
- Big Data: Apache Spark, Hadoop, Databricks, Snowflake, etc.
- Cloud: AWS (Glue, Redshift), Azure (Synapse, Data Factory).
Data Engineering Consultant in London - Endava employer: WorksHub
Contact Detail:
WorksHub Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Consultant in London - Endava
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as PostgreSQL, MongoDB, and Apache Spark. Having hands-on experience or projects showcasing these skills can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work at Endava or similar companies. Attend industry meetups or webinars to make connections and learn more about the company culture and expectations.
✨Tip Number 3
Prepare for technical interviews by practising coding challenges in Python, SQL, and Scala. Websites like LeetCode or HackerRank can help you sharpen your skills and get comfortable with common data engineering problems.
✨Tip Number 4
Showcase your understanding of DevOps practices by discussing any relevant experience with Docker, Kubernetes, or CI/CD pipelines during interviews. Being able to articulate how these tools improve data workflows will demonstrate your value to the team.
We think you need these skills to ace Data Engineering Consultant in London - Endava
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with technologies mentioned in the job description like PostgreSQL, MongoDB, and Apache Spark. Use specific examples to demonstrate your skills.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your background in programming languages such as Python and SQL aligns with the requirements. Be sure to include any experience with DevOps tools like Docker and Kubernetes.
Showcase Your Projects: If you have worked on projects involving data modelling or cloud services like AWS or Azure, include these in your application. Describe your role and the impact of your contributions to demonstrate your hands-on experience.
Highlight Continuous Learning: Mention any relevant certifications or courses you've completed related to data engineering, big data technologies, or cloud platforms. This shows your commitment to staying updated in the field and can set you apart from other candidates.
How to prepare for a job interview at WorksHub
✨Showcase Your Technical Skills
Be prepared to discuss your experience with the specific technologies mentioned in the job description, such as PostgreSQL, MongoDB, and Apache Spark. Highlight any projects where you've successfully implemented these tools, as this will demonstrate your hands-on expertise.
✨Understand Data Modelling Concepts
Since the role involves data modelling, brush up on dimensional and relational modelling techniques. Be ready to explain how you approach designing data models and how you ensure data quality and integrity in your work.
✨Familiarise Yourself with DevOps Practices
The position requires knowledge of DevOps tools like Docker and Kubernetes. Make sure you can discuss how you've used these tools in past projects, particularly in automating data flows and managing CI/CD pipelines.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about challenges you've faced in previous roles related to data ownership and stewardship, and be ready to share how you addressed them effectively.
