Lead Data Engineer: Real-Time ML & Feature Store

Entravision Communications Corporation; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, Vision benefits

Travel to Barcelona HQ after year

Competitive US-market compensation

Job summary

Entravision’s Smadex unit seeks a Data Engineering Team Lead to steer two sub-teams—Data Quality and Feature Engineering—toward scalable, real-time data pipelines and ML feature serving.

You will mentor engineers, architect robust data platforms, and partner with CDO/CTO to align tech with business goals. Based in Austin, you’ll own end-to-end data workflows and data governance across global deployments.

Qualifications

• 6+ years of experience in software or data engineering, with at least 2 years in leadership building high-throughput distributed systems.
• Deep mastery of Spark and ability to conduct deep code reviews.
• Big data expertise designing and optimizing batch and streaming pipelines with Spark.
• Advanced SQL knowledge; cloud experience with AWS (EMR, EC2, Athena, S3).
• Analytical leadership to debug distributed systems and drive root-cause analysis.
• Excellent English communication translating complex tech to stakeholders.

Responsibilities

• Lead and scale two sub-teams: Data Quality and Feature Engineering, including hiring and career growth.
• Design scalable data pipelines bridging storage and real-time ML inference.
• Define and execute a technical roadmap for data platforms and feature stores.
• Oversee Data Quality, observability, testing, and data ingestion reliability.
• Coordinate with infrastructure to run complex DAGs in Airflow and ensure operational excellence.

Skills

Spark

Scala

Python

Bash

Distributed systems

AWS

Airflow

Docker

Kubernetes

SQL

Education

Master’s degree in Computer Science or Engineering

Tools

Docker

Kubernetes

Airflow

Git

Jira

Notion

Job description

Entravision’s Smadex unit seeks a Data Engineering Team Lead to steer two sub-teams—Data Quality and Feature Engineering—toward scalable, real-time data pipelines and ML feature serving.

You will mentor engineers, architect robust data platforms, and partner with CDO/CTO to align tech with business goals. Based in Austin, you’ll own end-to-end data workflows and data governance across global deployments.