Job Description
As a Data Engineering Team Lead, you'll be key in helping us scale to meet customer demands. Working with other Data Engineering Leads you’ll get to shape how we work, recommend standards and ways of working, and build up a thriving community around you. You will be directly involved in customer projects where engagements are varied and cutting-edge technologies are always present.
1. Manage a team of up to 50 people, covering project staffing allocations, chargeability reporting, staff wellbeing, and staff development needs.
2. Consult in data architecture and engineering delivery roles for customers and be “hands-on” with projects.
3. Provide leadership, coaching, and mentoring for Data Engineering team members to support their continual development.
4. Identify and drive improvements and innovations within your team and work with the wider Version 1 organisation (OCTO etc.) to bring additional value.
5. Support Portfolio Directors and Commercial colleagues to provide advice across all aspects of engagements: compiling and reviewing estimates, presales responses, reviewing TORs/SOWS, and mobilising staffing needs.
6. Promote cooperation and knowledge sharing amongst the Version 1 teams and provide a consistent and uniform approach to technology.
7. Support marketing, content, webinars, lunch & learns, and speaking at events to support building of the Version 1 brand.
8. Establish a good working relationship with and support Version 1 staff; help retain our people and build a community where people want to stay and grow their career.
Qualifications
Essential Criteria:
9. Deep technical expertise in Data Engineering including In-depth knowledge of Data Engineering practices, including Data Storage, Data Visualization, ETL, Data Integration & Migration, Data Warehousing, and Business Intelligence.
10. Familiarity with Data Engineering security, data ethics, and legal/compliance frameworks.
11. Proven experience in driving innovation, with a focus on emerging technologies such as AI & ML.
12. Ability to define best practices and methodologies in Data Engineering, staying abreast of industry trends.
13. Working knowledge of the Cloud Adoption Framework and Well Architected Framework.
14. Strong communication skills with the ability to develop thought leadership materials, including whitepapers, blogs, webinars, etc.
15. Proficiency in defining and documenting reference architectures, solution designs, and accelerators for Data Solutions.
16. Experience in maintaining technical governance and oversight for solution design and implementation.
17. Experience in capacity planning and succession planning to manage workloads effectively.