3d ago
Senior Data Engineering (Tech Lead)
Senior Data Engineering (Tech Lead)
Senior Data Engineering (Tech Lead)
Requirements
Qualifications
Data Engineering Experience
- Master’s degree (or equivalent) in Computer Science, Engineering, or a related field.
- 7+ years of experience as a Data Engineer, including at least 1 year in a Tech Lead or similar leadership role.
- Strong expertise in database design, data modeling, and handling both structured and unstructured data.
- Strong system design and architectural skills, with the ability to design scalable data platforms.
- Proficiency in SQL and Python, with solid experience building and maintaining ETL/ELT pipelines.
- Familiarity with modern data stack tools such as dbt, AWS Lambda, Step Functions, Glue, Athena, Redshift, or similar.
- Exposure to telemetry data systems and large-scale product analytics.
- Experience building internal data platforms or self-service analytics solutions.
- Hands-on experience with the AWS cloud platform.
- Experience with data visualization tools such as Power BI, QuickSight, Tableau, or similar.
- Practical knowledge of DevOps practices, CI/CD pipelines, and tools such as Git.
- Experience with containerization and infrastructure tools (e.g., Docker, Terraform, Jenkins).
- Proven ability to own projects end-to-end and operate with a high level of autonomy.
- Excellent communication and collaboration skills, with fluency in English.
AI & Advanced Capabilities
- Experience building and deploying AI-powered data systems, including Retrieval-Augmented Generation (RAG) and LLM-based applications.
- Familiarity with LLM frameworks (e.g., LangChain, LlamaIndex) and integrating LLM APIs into production workflows.
- Experience designing AI agents or intelligent data interfaces (e.g., chat-to-data, NL-to-SQL).
- Understanding of semantic data modeling to enable natural language interaction with structured data.
- Ability to evaluate, monitor, and scale AI systems, with strong architectural judgment for integrating AI into data platforms.
Benefits
Additional Information
We are the pioneers and trailblazers of a global IT Market Category (DEX) that is shaping the future of how the world works, giving our customers’ IT Teams total digital visibility across their enterprise. Our innovative solutions integrate real-time analytics, automation, and employee feedback across all endpoints. This enables our IT teams to solve complex technical challenges, create ever more productive workplaces, and deliver happy, satisfied employees in the digital workplace.
Original Advert
Company Description
Nexthink is the leader in digital employee experience management software. The company provides IT leaders with unprecedented insight allowing them to see, diagnose and fix issues at scale impacting employees anywhere, with any application or network, before employees notice the issue. As the first solution to allow IT to progress from reactive problem solving to proactive optimization, Nexthink enables its more than 1,300 customers to provide better digital experiences to more than 18 million employees. Dual headquartered in Lausanne, Switzerland and Boston, Massachusetts, Nexthink has 9 offices worldwide.
Job Description
The Product Intelligence team serves a critical role by providing business intelligence to the organization: we synthesize data sources across the company, delivering product usage and business insights that directly shape product strategy and decision-making.
We are looking for a Senior Data Engineering (Tech Lead) to lead our team of data engineers and to bring your experience and vision in data warehouse design, data modeling, and data visualization. We are seeking an individual with a strong data background but also an AI-first mentality, who can drive our current initiatives to leverage AI for accelerating modeling and dashboarding tasks, as well as exposing our telemetry data to stakeholders across the company in the form of an AI agent and MCP.
What you'll do
- Partner with the Product Manager to shape the roadmap, refine scope, and define clear, actionable acceptance criteria.
- Own the technical architecture for data warehousing, data modeling, and data access patterns.
- Lead the team technically to design, implement, deliver, and validate scalable data pipelines and reporting solutions.
- Drive the design and evolution of the analytics layer, including semantic modeling and dashboarding within BI tools.
- Define and implement an AI-first approach to data, including AI-assisted workflows for modeling, analysis, and dashboard creation.
- Architect and deliver an AI-powered interface (agent) that enables stakeholders to access and explore telemetry data in a self-service manner.
- Enable integration of telemetry insights into internal tools and workflows by providing and maintaining supporting capabilities (e.g., MCP or equivalent interfaces).
- Establish data engineering standards, best practices, and measurable quality indicators to ensure high-quality, maintainable code.
- Ensure scalability, reliability, and performance of data platforms, pipelines, and analytics workloads.
- Mentor and support data engineers through technical guidance, code reviews, and knowledge sharing.
- Promote an agile, iterative engineering culture and actively contribute to team ceremonies.
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