Data Engineering Manager

Job Description

As an Engineering Manager on our Audience Engineering team, you will build solutions that add new data capabilities and analytical depth to our platform while managing sophisticated AWS-native data services.

You will :

– Architect Scalable Pipelines : Oversee the design and deployment of large-scale distributed data processing jobs using PySpark on Amazon EMR clusters and serverless AWS Glue ETL jobs.

– Coach and mentor engineerssupporting growth in technical skills (particularly Python and Spark optimization), data modeling best practices, and career progression.

– Partner with stakeholders and engineering leadership to evaluate, plan, and deliver data-first projects across advertising systems, analytics services, and reporting features.

– Lead by example : Write production-ready Python and PySpark code, perform code reviews, and optimize Spark configurations to improve performance and reduce costs.

– Apply Agile methodologies such as Scrum to drive iterative development, foster team collaboration, and ensure continuous delivery of high-quality data solutions.

– Support engineers through regular 1:1s, feedback, quarterly reviews, recognition, and performance management.

You have :

– Bachelors degree in Computer Engineering, Data Science, or equivalent practical experience.

– 8+ years of experience in technology, specifically focused on data engineering, data warehousing, or big data architecture.

– 2+ years of experience of leading a data engineering team.

– Expertise in Python & PySpark : Deep experience writing and tuning distributed processing applications, handling data skew, and optimizing Spark memory management.

– Advanced AWS Expertise : Proven track record of managing Amazon EMR for heavy-duty processing.

– Experience with Big Data Infrastructure : Build the systems required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies (S3, EMR, Glue, Athena and Lambda).

– Expert SQL skills for complex transformations, performance tuning, and deep-dive analytics.

– Experience with Orchestration : Advanced proficiency with Airflow and Git.

– AI-Driven Engineering : Proven track record of leveraging AI across the data engineering process to drive modernization, automate data quality checks, and enhance delivery outcomes.

– Hands-on familiarity with AI-native tools such as Cursor, Claude, or GitHub Copilot to scale data development.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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