Team Lead (Data/AI)
The Team Lead in Data & AI serves as a player-coach for a focused group of engineers or analysts. They split time between hands-on engineering or architectural design and day-to-day team coordination, code reviews, and unblocking colleagues.
The Team Lead in Data & AI serves as a player-coach for a focused group of engineers or analysts. They split time between hands-on engineering or architectural design and day-to-day team coordination, code reviews, and unblocking colleagues.
The role demands technical depth in data engineering or applied ML paired with mentoring skills, clear communication, and the ability to keep sprint deliveries on track.
Methodologies & technical foundations (% penetration)
Infrastructure & tooling demanded in job specs (% penetration)
Seniority Level Breakdown
Corporate hierarchy distribution
Top Hiring Enterprises
Leading corporations posting this role
- IQVIA14 positions
- Citigroup13 positions
- UnitedHealth Group10 positions
- Google (Alphabet)4 positions
- TE Connectivity4 positions
- Alphabet Inc. (Class C)4 positions
S&P 500 Sector Distribution
Industry sectors generating the highest hiring demand
- Health Care33.8%
- Financials29.6%
- Communication Services16.9%
- Consumer Discretionary7%
- Information Technology5.6%
Live Enterprise Job Postings
Sample of active postings directly from corporate ATS boards
Data and AI Solutions Sales Lead
AI Software Engineering Lead
Tech, Data, Digital and Partnerships Lead
Data Center Delivery Crew Lead
Third-Party Data Management Lead
Data Privacy Delivery Lead
Data Engineer Lead - Cloud Architecture
AVP - KYC Operations Artificial Intelligence (AI) Lead
Recommended Skill Tracks & Certifications
Curated programs on Coursera, DataCamp and cloud providers aligned with these role requirements
Data Engineer with Python Career Track
Interactive, browser-based coding track covering robust data pipelines, PostgreSQL, unit testing, software design patterns for data, and PySpark fundamentals.
Generative AI with Large Language Models
Created by Andrew Ng and AWS: practical engineering foundations of transformer architectures, pre-training, instruction fine-tuning, and alignment evaluation in production.
Analytics Engineering with dbt & SQL
Bridge the gap between raw data analysis and software-grade transformations. Learn modular dimensional modeling, automated testing assertions, and Git-driven CI/CD.
Databricks Certified Data Engineer Professional
Validates mastery of streaming, batch ETL, Unity Catalog governance, and production Lakehouse architectures with Delta Lake and Spark.