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- Tasks: Lead the design and development of scalable data pipelines for innovative applications.
- 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: Dynamic team environment with a focus on continuous learning and cutting-edge technologies.
- Why this job: Make an impact by shaping AI-powered features and mentoring future data engineers.
- Qualifications: 7+ years in data engineering with leadership experience and strong technical skills.
The predicted salary is between 90000 - 120000 £ per year.
We are seeking a highly skilled and experienced Lead Data Engineer to join our talented team. The ideal candidate will have a strong background in data engineering, with experience in AI and a proven track record of designing and implementing robust data pipelines.
Responsibilities
- Lead the design, development, and maintenance of scalable and efficient data pipelines to support our data-driven applications.
- Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to understand data requirements and deliver high-quality solutions.
- Architect and implement data ingestion, transformation, and storage processes using tools such as Apache Spark, Azure Data Factory, and other similar technologies.
- Optimize data pipeline performance, ensuring data accuracy, reliability, and timely delivery.
- Mentor and guide junior data engineers, fostering a culture of continuous learning and improvement.
- Stay up-to-date with the latest trends and best practices in data engineering and AI, and apply them to our projects.
- Participate in the evaluation and selection of new technologies and tools to enhance our data engineering capabilities.
- Contribute to the development of AI-powered features and products, leveraging your knowledge of machine learning and data science concepts.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 7+ years of experience in data engineering, with at least 3 years in a leadership role.
- Strong proficiency in Apache Spark, Azure Data Factory, and other data pipeline tools.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Solid understanding of data modeling, data warehousing, and ETL/ELT processes.
- Familiarity with AI and machine learning concepts, with hands-on experience in implementing AI-driven solutions.
- Excellent problem-solving skills and the ability to design and optimize data architectures.
- Strong programming skills in languages such as Python, Scala, or Java.
- Experience with data quality, data governance, and data security best practices.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
- Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities.
Preferred Qualifications
- Advanced degree in Computer Science, Data Science, or a related field.
- Certifications in relevant technologies, such as Azure Data Engineer or Databricks Certified Developer.
- Experience with real-time data processing and streaming technologies like Apache Kafka or Azure Event Hubs.
- Knowledge of data visualization tools, such as Power BI or Tableau.
- Contributions to open-source projects or active participation in the data engineering community.
Director: Lead Data Engineer employer: ESP Engineered
Contact Detail:
ESP Engineered Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Director: Lead Data Engineer
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in a data engineering role. You never know when a casual chat could lead to your next big opportunity.
✨Show Off Your Skills
Don’t just talk about your experience; showcase it! Create a portfolio of projects that highlight your expertise in data pipelines and AI. This can really set you apart from other candidates and give us a glimpse of what you can bring to the table.
✨Ace the Interview
Prepare for those interviews by brushing up on common data engineering questions and scenarios. Be ready to discuss your past projects and how you tackled challenges. Remember, we want to see your problem-solving skills in action!
✨Apply Through Our Website
Make sure to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Director: Lead Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match our job description. Highlight your data engineering expertise, especially with tools like Apache Spark and Azure Data Factory, to show us you’re the right fit!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how your leadership experience can help us build robust data pipelines. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool data projects, don’t hold back! Share specific examples of your work, especially those involving AI or machine learning. We love seeing how you’ve tackled challenges and delivered results.
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 ESP Engineered
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tools mentioned in the job description, like Apache Spark and Azure Data Factory. Brush up on your knowledge of data pipelines and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Leadership Skills
As a Lead Data Engineer, you'll need to demonstrate your ability to mentor and guide junior engineers. Prepare examples of how you've led teams or projects, and be ready to discuss your approach to fostering a culture of continuous learning.
✨Collaborate Like a Pro
Highlight your experience working with cross-functional teams. Be prepared to talk about how you’ve collaborated with data scientists, software engineers, and product managers to deliver high-quality solutions that meet data requirements.
✨Stay Current with Trends
The field of data engineering and AI is always evolving. Show your enthusiasm for staying up-to-date with the latest trends and best practices. Mention any recent technologies or methodologies you've explored and how they could benefit the company.