Principal Data Engineer — Hybrid, AI & Analytics

Analog Devices, Inc.; Wilmington, Northern (MA, KY); Hybrid; USD 217,000 - 251,000; Full time

Benefits offered by this job

Partial telecommute

Job summary

Analog Devices, Inc. seeks a Principal Engineer, Data Engineering to own end-to-end data architecture enabling AI and analytics across diverse applications. Lead data modeling, ingestion, storage, transformation and governance while mentoring engineers and coordinating with AI/ML and software teams.

The role focuses on scalable, observable data platforms with security and quality as core values; partial telecommute is offered, with two days remote per week.

Qualifications

• Master’s or Bachelor’s with extensive data product lifecycle experience.
• Expertise in distributed systems, streaming, and data tooling.
• Strong knowledge of cloud data architectures and governance.

Responsibilities

• Lead end-to-end data architecture for scalable AI analytics.
• Set standards for data modeling, ingestion, storage and transformation.
• Drive data quality, observability and governance across domains.
• Mentor data engineers and collaborate with AI/ML teams to deploy models.

Skills

Distributed Systems

Spark

Kubernetes

Terraform

Kafka

Pub Sub

Airflow

Hadoop

Looker

Tableau

Business Objects

GCP

Azure

AWS

Data Governance

Data Quality

Observability

ML concepts

Education

Master’s degree in Information Technology, Computer Science, Electrical Engineering, Computer Engineering, or related field

Bachelor’s degree in Information Technology, Computer Science, Electrical Engineering, Computer Engineering, or related field with 5+ years experience

Tools

Informatica

Talend

SQL

Python

Oracle

SQL Server

Vertica

Looker

AtScale

Tableau

Business Objects

GCP BigQuery

Dataflow

Azure Synapse

Fabric

Redshift

Glue

Job description

Analog Devices, Inc. seeks a Principal Engineer, Data Engineering to own end-to-end data architecture enabling AI and analytics across diverse applications. Lead data modeling, ingestion, storage, transformation and governance while mentoring engineers and coordinating with AI/ML and software teams.

The role focuses on scalable, observable data platforms with security and quality as core values; partial telecommute is offered, with two days remote per week.