Software Engineering Manager

AbbVie, Inc•San Francisco, CA

45d

About The Position

About the Role The Data Platform team builds and maintains the foundation that powers analytics, ML, and data-driven products. As part of Platform Engineering, our mission is to enable other teams to move faster, safer, and with greater reliability by delivering scalable, observable, and compliant data systems. We're seeking a Manager, Data Platform with strong technical expertise and 2-4 years of leadership experience. You'll own the evolution of the data ecosystem from ingestion and transformation pipelines to data modeling and event-driven systems, ensuring performance and stability at scale. You will mentor engineers while staying hands-on with architecture and implementation. Who You Are You're a systems-minded leader who blends architectural vision with hands-on execution. You build for scale, reliability, and simplicity. Enabling teams across the organization to deliver trusted, high-quality data with confidence and speed.

Requirements

Bachelor's Degree required
8-10 years total experience in data, software, and platform engineering roles.
2-4 years of experience leading or managing technical teams.
Proficiency in Python and TypeScript for data pipeline and backend service development.
Expertise in PostgreSQL, including schema design, query optimization, and replication.
Deep understanding of data modeling, ETL/ELT frameworks, and event-driven architecture.
Hands-on experience with Kafka, Terraform, and AWS data services.
Proven success operating and scaling production data systems with high reliability and observability.

Responsibilities

Lead and grow a team of data and software platform engineers, fostering technical excellence, ownership, and collaboration.
Define and execute the data platform roadmap, covering ingestion, transformation, orchestration, and data access.
Design, implement, and maintain ETL/ELT pipelines and data models that support analytics, ML, and operational workloads.
Architect and evolve event-driven data systems using Kafka to enable scalable, decoupled pipelines.
Maintain and optimize core data tooling such as Snowflake, dbt, Airflow, and Fivetran.
Ensure system reliability, observability, and performance across development, staging, and production environments.
Partner with domain and product engineering teams to define and enforce data contracts, governance, and quality standards.
Manage AWS-based infrastructure (MWAA, S3, RDS/Postgres, MSK, Glue, Lambda, ECS/EKS) using Terraform.
Collaborate with Platform and Security Engineering on CI/CD, monitoring, and compliance practices.
Champion automation, scalability, and cost efficiency within the platform.