Senior Data Services Engineer
Content + Source + Freshness • 16 Dec 2025 • 95% confidence
Offer value
Decent offer with an emphasis on mentorship and technical expertise, but requires strong analytical skills and domain knowledge.
- Opportunity to mentor junior engineers
- Engagement in AI model deployment
- Requires 4-5 years of relevant experience
- Potentially high-pressure client interactions
Pros
- Opportunity to serve as a technical expert and mentor to junior engineers, enhancing leadership skills.
- Work on the deployment of AI models which is increasingly relevant in today’s data landscape.
- Clear responsibilities that outline both technical and client-facing roles.
Cons
- Requires extensive experience (4-5 years) which may deter entry-level candidates.
- Potentially high-pressure environment due to client-facing responsibilities.
- Moderate salary range compared to other tech roles in the industry.
Who it's for
Mid-level • Hybrid/On-site
Good fit
- Technical consultants with data experience
- Individuals who enjoy mentoring and client engagement
- Professionals keen on AI advancements
Not recommended for
- New graduates without relevant experience
- Those preferring solely technical roles
- Candidates who do not handle pressure well
Motivation fit
Key skills
About the job
• Model Implementation & Client Success: Lead the end-to-end design, training, and successful deployment of high-performance AI models, ensuring implementation plans meet strategic client goals.
• Data Quality & Process Ownership: Independently execute complex data annotation and Quality Assurance (QA) projects, while defining and championing best practices and operational guidelines for the team.
• Technical Expertise & Mentorship: Serve as the primary technical expert, handling complex escalations and troubleshooting, while mentoring junior engineers on technical execution and best practices.
• Cross-Functional Impact: Act as a critical liaison, translating client needs to technical solutions and providing actionable product feedback and performance insights to internal Product, Design, and Engineering teams.
Requirements
- Experience & Scope: 4-5 years of progressive experience in a technical consulting or customer-facing software services role, including proven expertise in enterprise implementation and technical escalation management.
- Core Professional Skills: Strong demonstrated analytical, problem-solving, and collaboration skills, with excellent verbal and written communication suitable for both technical teams and client audiences.
- Technical Acumen: Proven ability to rapidly learn and master new software platforms and interfaces, coupled with meticulous attention to detail and proficiency in spreadsheet tools (e.g., Excel/G-Sheets).
- Bonus Qualifications: Relevant degree (or equivalent ongoing studies) in a technical field such as IT, Economics, Business Administration, or related disciplines.
- ML Model Experience: Direct experience with training and iterating Machine Learning models is highly beneficial.
🔍 ATS Optimization Keywords
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Hard Skills
- AI model deployment
- data annotation
- Quality Assurance (QA)
- technical escalation management
- Machine Learning model training
- analytical skills
- problem-solving skills
- collaboration skills
- attention to detail
- proficiency in spreadsheet tools
Soft Skills
- mentorship
- verbal communication
- written communication
- client liaison
- actionable feedback
