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- Tasks: Join our team as a Data Engineer, designing efficient data pipelines and optimising cloud infrastructure.
- Company: We are a dynamic company focused on leveraging data for business success.
- Benefits: Enjoy remote work flexibility and the chance to work with cutting-edge technologies.
- Why this job: This role offers a fast-paced environment and the opportunity to make a real impact with data.
- Qualifications: 10+ years of experience in data engineering and a relevant degree are required.
- Other info: Contract duration is 4 months with potential for extension; start ASAP.
The predicted salary is between 54000 - 84000 £ per year.
Duration of Contract – 4 months with possible extension
Start Date: ASAP
Experience Level: 10+ Years
We are seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team. The ideal candidate should have a robust background in the various phases of ETL data applications, including data ingestion, preprocessing, and transformation. This role is perfect for someone who thrives in a fast-paced environment and is passionate about leveraging data to drive business success.
Key Responsibilities:
- Design and implement efficient data ingestion pipelines to collect and process large volumes of data from various sources.
- Hands-on experience with AWS Database Migration Service for seamless data migration between databases.
- Develop and maintain scalable data processing systems, ensuring high performance and reliability.
- Utilize advanced data transformation techniques to prepare and enrich data for analytical purposes.
- Collaborate with cross-functional teams to understand data needs and deliver solutions that meet business requirements.
- Manage and optimize cloud-based infrastructure, particularly within the AWS ecosystem, including services such as S3, Step-Function, EC2, and IAM.
- Experience with cloud platforms and understanding of cloud architecture.
- Knowledge of SQL and NoSQL databases, data modelling, and data warehousing principles.
- Familiarity with programming languages such as Python or Java.
- Implement security and compliance measures to safeguard data integrity and privacy.
- Monitor and tune the performance of data processing systems to ensure optimal efficiency.
- Stay updated with emerging trends and technologies in data engineering and propose adaptations to existing systems as needed.
- Proficient in AWS Glue for ETL (Extract, Transform, Load) processes and data cataloging.
- Hands-on experience with AWS Lambda for serverless computing in data workflows.
- Knowledge of AWS Glue Crawler Kinesis RDS for batch / real-time data streaming.
- Familiarity with AWS Redshift for large-scale data warehousing and analytics.
- Skillful in implementing data lakes using AWS Lake Formation for efficient storage and retrieval of diverse datasets.
- Experience with AWS Data Pipeline for orchestrating and automating data workflows.
- In-depth understanding of AWS CloudFormation for infrastructure as code (IaC) deployment.
- Proficient in AWS CloudWatch for monitoring and logging data processing workflows.
- Familiarity with AWS Glue DataBrew for visual data preparation and cleaning.
- Expertise in optimizing data storage costs through AWS Glacier and other cost-effective storage solutions.
- Hands-on experience with AWS DMS (Database Migration Service) for seamless data migration between different databases.
- Knowledge of AWS Athena for interactive query processing on data stored in Amazon S3.
- Experience with AWS AppSync for building scalable and secure GraphQL APIs.
Qualifications:
A minimum of 10 years of experience in data engineering or a related field. Strong background in big data application phases, including data ingestion, preprocessing, and transformation.
Education:
Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field. A Master’s degree is preferred.
002AVM - Data Engineer (Remote) employer: Augusta Hitech
Contact Detail:
Augusta Hitech Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land 002AVM - Data Engineer (Remote)
✨Tip Number 1
Make sure to showcase your hands-on experience with AWS services in your conversations. Highlight specific projects where you've implemented data ingestion pipelines or used AWS Glue for ETL processes, as this will resonate well with our team.
✨Tip Number 2
Familiarise yourself with the latest trends in data engineering and be prepared to discuss how you can apply these to improve our existing systems. Showing that you're proactive about learning can set you apart from other candidates.
✨Tip Number 3
During interviews, emphasise your ability to collaborate with cross-functional teams. Share examples of how you've successfully worked with different departments to meet data needs, as teamwork is crucial in our dynamic environment.
✨Tip Number 4
Be ready to discuss your experience with both SQL and NoSQL databases. Providing concrete examples of how you've utilised these technologies in past projects will demonstrate your versatility and depth of knowledge in data engineering.
We think you need these skills to ace 002AVM - Data Engineer (Remote)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your extensive experience in data engineering, particularly focusing on ETL processes, AWS services, and any relevant programming languages like Python or Java. Use specific examples to demonstrate your skills.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your background aligns with the job requirements. Mention your experience with AWS tools and your ability to work in fast-paced environments.
Showcase Relevant Projects: If you have worked on significant projects involving data ingestion, transformation, or cloud infrastructure, be sure to include these in your application. Highlight your role and the impact of your contributions.
Proofread Your Application: Before submitting, carefully proofread your application materials for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial in data engineering roles.
How to prepare for a job interview at Augusta Hitech
✨Showcase Your ETL Expertise
Be prepared to discuss your experience with ETL processes in detail. Highlight specific projects where you designed and implemented data ingestion pipelines, and explain the challenges you faced and how you overcame them.
✨Demonstrate Cloud Proficiency
Since the role heavily involves AWS services, brush up on your knowledge of AWS tools like Glue, Lambda, and Redshift. Be ready to share examples of how you've used these services in past projects to solve real-world problems.
✨Prepare for Technical Questions
Expect technical questions related to SQL, NoSQL databases, and data modelling. Practise explaining complex concepts in simple terms, as you may need to collaborate with cross-functional teams who might not have a technical background.
✨Stay Updated on Trends
Research the latest trends in data engineering and be ready to discuss how they could apply to the company's needs. Showing that you're proactive about learning can set you apart from other candidates.
