Senior Data Engineer (SQL DBA & Team Lead)

M3 Global Research
London
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - Energy

Senior Data Engineer, SQL, RDBMS, AWS, Python, Mainly Remote

Senior Data Engineer (2 days onsite in London)

Senior Data Engineer

About M3:A Japanese global leader in the provision of ground-breaking and innovative technological and research solutions to the healthcare industry. The M3 Group operates in the US, Asia, and Europe with over 5.8 million physician members globally via its physician websites which include mdlinx.com, m3.com, research.m3.com, Doctors.net.uk, medigate.net, and medlive.cn. M3 Inc. is a publicly traded company on the Tokyo Stock Exchange (jp:2413, NIKKEI 225) with subsidiaries in major markets including the US, UK, Japan, South Korea, and China, and in 2020 was ranked in Forbes’ Global 2000 list. The M3 Group provides services to healthcare and the life science industry. In addition to market research, these services include medical education, ethical drug promotion, clinical development, job recruitment, and clinic appointment services. M3 has offices in Japan, UK, France, Germany, Brazil, Sweden, China, USA, and South Korea, as well as India.

M3 Global Research, an M3 company, is seeking a Senior Data Engineer with SQL DBA expertise to join our data engineering team. This role will primarily focus on database administration (DBA) tasks such as optimization, performance tuning, and security while also leading a team of Power BI and Data Engineers.

Job Description:

The ideal candidate will have strong SQL database administration expertise while also acting as the public-facing lead for the Power BI/Data Engineering team. They will be responsible for understanding business needs, prioritizing work, leading daily stand-ups, and effectively communicating technical solutions to stakeholders. While direct Power BI development is not required, the candidate should be able to guide and support the team’s work and ensure alignment with business objectives.

This role is designed as a team lead position with the potential to grow into a management role in the future.

Primary DBA Responsibilities:

  • Manage and optimize databases (SQL Server, PostgreSQL, Oracle) for performance, security, and availability.
  • Design and maintain database schemas, indexes, and partitions to support scalability and efficiency.
  • Perform database monitoring, backup, recovery, and disaster recovery planning.
  • Implement security best practices, including access control, encryption, and auditing.
  • Troubleshoot database performance issues and optimize query performance.
  • Ensure compliance with data governance, security policies, and industry standards.

Team Leadership Responsibilities:

  • Act as the public-facing lead for the Power BI/Data Engineering team, effectively communicating with business stakeholders.
  • Conduct daily stand-ups, prioritize tasks, and ensure the team is aligned with business needs.
  • Translate business requirements into actionable data engineering tasks.
  • Work closely with cross-functional teams to ensure that Power BI and data solutions meet business objectives.
  • Mentor team members and drive best practices in data management and reporting.

Qualifications:

  • Strong SQL database administration expertise (performance tuning, security, backup/recovery).
  • Excellent communication and leadership skills to work with both technical and non-technical teams.
  • Ability to prioritize and manage a team’s workload while driving business objectives.
  • Problem-solving mindset with a strong attention to detail.

Additional Information:

#LI-LC1
#LI-Remote

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.