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- Tasks: Manage AWS data processes and optimize data flows for business intelligence.
- Company: Join a dynamic team focused on leveraging data to drive business success.
- Benefits: Enjoy remote work flexibility and competitive pay at £500 per day.
- Why this job: Be at the forefront of data engineering, impacting real-time decision-making.
- Qualifications: Proficient in MySQL, Apache Kafka, AWS Glue, PySpark, and BI reporting.
- Other info: Ideal for those who thrive in collaborative environments with non-technical teams.
The predicted salary is between 72000 - 108000 £ per year.
Job Title : Data Engineer Location : Remote Contract : £500 Per Day Role Overview Our client is seeking a Data Engineer with a solid foundation in both data engineering and business intelligence, capable of understanding and addressing business needs. This role involves managing and optimizing AWS-based data processes, orchestrating data flows, and supporting business intelligence capabilities. The ideal candidate will not only bring technical expertise but also a strong business acumen to facilitate effective collaboration with non-technical stakeholders. Key Responsibilities Data Pipeline Management : Database Integration : Maintain MySQL databases on AWS (approx. 25TB) as primary data sources feeding the data pipeline. Real-Time Data Ingestion : Utilize Apache Kafka to manage data flows from MySQL into AWS S3 buckets, enabling real-time streaming. Data Processing : Implement ETL processes using AWS Glue and PySpark to build data lakes within S3 for further analysis. Business Intelligence (BI) : Facilitate data availability for BI purposes, supporting daily updates and aiming to move from overnight batch jobs to near-real-time 15-minute refreshes. Collaborate on BI dashboard and reporting creation to provide actionable insights. Complex Data Reconciliation : Reconcile transaction records across multiple merchants, currencies, and network operators, addressing both straightforward and complex data relationships. Technical Requirements Data Engineering Expertise : Proficiency with MySQL , Apache Kafka , AWS Glue , PySpark , and AWS S3 for managing data pipelines and ETL processes. Business Intelligence Skills : Experienced in designing and maintaining BI reports and dashboards with frequent data refresh capabilities. Data Reconciliation Experience : Skilled in reconciling transactional data across diverse systems, operators, and currencies to ensure data accuracy. Business & Communication Skills Business Acumen : Ability to translate business requirements into data solutions and work collaboratively with non-technical stakeholders to develop reports and dashboards tailored to business needs. Communication : Strong communication skills to bridge technical and business needs, working closely with stakeholders to ensure data solutions support strategic objectives.
Senior Data Engineer employer: TalentHawk
Contact Detail:
TalentHawk Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Familiarize yourself with AWS services, especially AWS Glue and S3, as these are crucial for the role. Consider taking online courses or certifications to deepen your understanding of these tools.
✨Tip Number 2
Brush up on your MySQL skills, particularly in managing large databases. Being able to demonstrate your experience with database integration will set you apart from other candidates.
✨Tip Number 3
Gain hands-on experience with Apache Kafka for real-time data ingestion. Building a small project that showcases your ability to manage data flows can be a great talking point during interviews.
✨Tip Number 4
Develop your business acumen by understanding how data impacts decision-making in businesses. Being able to discuss how your technical skills can solve business problems will resonate well with non-technical stakeholders.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Senior Data Engineer position. Familiarize yourself with the technical skills needed, such as MySQL, Apache Kafka, AWS Glue, and PySpark.
Tailor Your CV: Customize your CV to highlight relevant experience in data engineering and business intelligence. Emphasize your proficiency with the required technologies and any previous projects that demonstrate your ability to manage data pipelines and support BI capabilities.
Craft a Compelling Cover Letter: Write a cover letter that showcases your technical expertise and business acumen. Explain how your background aligns with the company's needs and how you can contribute to their data processes and BI initiatives.
Highlight Communication Skills: In your application, emphasize your communication skills and ability to collaborate with non-technical stakeholders. Provide examples of how you've successfully translated business requirements into data solutions in past roles.
How to prepare for a job interview at TalentHawk
✨Showcase Your Technical Skills
Be prepared to discuss your experience with MySQL, Apache Kafka, AWS Glue, and PySpark. Highlight specific projects where you managed data pipelines or implemented ETL processes, as this will demonstrate your technical expertise.
✨Demonstrate Business Acumen
Prepare examples of how you've translated business requirements into data solutions in the past. Discuss your experience collaborating with non-technical stakeholders to create reports and dashboards that meet their needs.
✨Discuss Real-Time Data Processing
Since the role emphasizes real-time data ingestion, be ready to explain your experience with real-time data flows and how you've utilized tools like Apache Kafka to achieve this. Share any challenges you faced and how you overcame them.
✨Communicate Clearly
Strong communication skills are crucial for this position. Practice explaining complex technical concepts in simple terms, as you'll need to bridge the gap between technical and business teams effectively.
