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- Tasks: Lead a dynamic data engineering team and optimise data platforms using AWS.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Enjoy professional growth opportunities, a collaborative culture, and potential remote work options.
- Why this job: Shape the future of data engineering while making a real impact in the organisation.
- Qualifications: Proven leadership in data engineering, strong AWS knowledge, and excellent communication skills required.
- Other info: Ideal for those passionate about technology and continuous learning.
The predicted salary is between 48000 - 84000 £ per year.
We are seeking a Data Engineering Manager with a strong technical foundation, proven experience leading data engineering teams, and expertise in AWS platforms. This role demands a combination of operational management and strategic vision to drive the success of our data platforms and align with organizational goals.
Responsibilities
- People Management
- Team Building & Coaching: Foster a high-performing data engineering team through coaching, mentoring, and professional growth opportunities. Develop a leadership culture within the team, ensuring engagement and motivation.
- Stakeholder Engagement: Act as a visible advocate for data practices across teams. Confidently represent the data team and step in for senior leadership as needed.
- AWS Expertise: Hands-on experience with AWS services, scalable data solutions, and pipeline design. Strong coding skills in Python, SQL, and pySpark. Optimize data platforms and enhance operational efficiency through innovative solutions.
- Nice to Have: Background in software delivery, with a solid grasp of CI/CD pipelines and DataOps methodologies. Exposure to ML/AI implementations.
- Operational Excellence: Manage delivery timelines, performance metrics, and team operations effectively. Support technology upgrades, evaluate new tools, and adopt emerging trends.
- Strategic Vision: Shape the data engineering roadmap and transform vision into actionable outcomes. Collaborate across teams to ensure the data work delivers tangible business value.
- Attributes: Trustworthy, collaborative, and detail-oriented. Strong decision-making skills and a people-first approach. Positive mindset with a commitment to continuous learning.
Key Qualifications
- Proven experience in a technical leadership role within data engineering.
- Strong technical fluency and a problem-solving mindset.
- In-depth knowledge of AWS services and their practical implementation.
- Excellent communication and stakeholder management skills.
- Experience with performance metrics, delivery management, and team operations.
Data Engineering Manager employer: TalentHawk
Contact Detail:
TalentHawk Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Manager
✨Tip Number 1
Network with professionals in the data engineering field, especially those with experience in AWS. Attend industry meetups or webinars to connect with potential colleagues and learn about their experiences, which can give you insights into what we value at StudySmarter.
✨Tip Number 2
Showcase your leadership skills by discussing any previous team-building or coaching experiences during informal conversations. This could be through networking events or online forums where data professionals gather, as it demonstrates your ability to foster a high-performing team.
✨Tip Number 3
Stay updated on the latest trends in data engineering, particularly around AWS services and DataOps methodologies. Engaging in relevant online courses or certifications can not only enhance your skills but also provide talking points when you meet us or other industry professionals.
✨Tip Number 4
Prepare to discuss your strategic vision for data engineering in a conversational setting. Think about how you would align data initiatives with business goals, as this will resonate well with our focus on delivering tangible business value at StudySmarter.
We think you need these skills to ace Data Engineering Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, particularly your leadership roles and technical skills in AWS, Python, SQL, and pySpark. Use specific examples to demonstrate your achievements and how they align with the responsibilities of the Data Engineering Manager role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your vision for leading a team. Mention your experience in fostering high-performing teams and your strategic approach to data management. Be sure to connect your background with the company's goals.
Highlight Relevant Projects: In your application, include details about specific projects where you have successfully implemented AWS solutions or optimised data platforms. Discuss any experience with CI/CD pipelines and DataOps methodologies, as well as any exposure to ML/AI implementations.
Showcase Leadership Qualities: Emphasise your leadership style in your application. Highlight your ability to build trust, collaborate effectively, and make informed decisions. Provide examples of how you've motivated teams and driven operational excellence in previous roles.
How to prepare for a job interview at TalentHawk
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with AWS services, Python, SQL, and pySpark. Highlight specific projects where you optimised data platforms or designed scalable data solutions, as this will demonstrate your technical leadership capabilities.
✨Emphasise People Management Skills
Since the role involves team building and coaching, share examples of how you've fostered a high-performing team. Discuss your approach to mentoring and how you've created a culture of engagement and motivation within your previous teams.
✨Demonstrate Strategic Vision
Prepare to talk about how you've shaped data engineering roadmaps in the past. Be ready to explain how you transformed strategic visions into actionable outcomes and collaborated across teams to deliver business value.
✨Exhibit Strong Communication Skills
As stakeholder engagement is crucial, practice articulating your thoughts clearly and confidently. Be ready to discuss how you've acted as an advocate for data practices and represented your team in front of senior leadership.
