A Data Team Lead runs a mixed team of analysts and engineers that either powers business decisions or becomes the bottleneck. Your CV needs to show the infrastructure you built, how you moved data quality SLAs and whether dashboards are actually used. This template helps you tell that story without listing 40 tools.
Copy these as starting points and swap in your own numbers.
2024–2025 estimates. Wide ranges by experience and seniority.
Yes, at the level of reviews and architectural calls. If you stop coding entirely you lose context and authority. About 20 to 30% on hands-on work is a healthy balance.
Find concrete decisions: what product changed because of a dashboard, what experiments shipped, what processes got automated. Two or three solid cases beat vague claims.
At senior level you need both. Without business sense you build pipelines no one uses. Without technical depth you cannot make the right architectural calls.
Yes, if you touched it. ML infrastructure such as feature stores and MLOps is increasingly expected from senior Data Leads. Be honest about depth: tactical ML, not deep research.
Frame it through outcomes: cost, latency, query speed, downtime. Example: 'migrated 600 models from Redshift to Snowflake in 4 months with no downtime, cutting cost by 38%'.