Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $12 billion in FY22 and approximately 25,000 people globally working alongside 125,000 global customers, ADI ensures today’s innovators stay Ahead of What’s Possible.

Analog Device’s CoreAI team is looking for a Principal Data Engineer who will be responsible for defining governance for data pipelines and quality control of future tech datasets. They will also help define and develop technical controls for data collection, data quality control, and compliance. 

Responsibilities: 

• Define and develop technical controls for data collection, data quality control, and compliance to enable modern AI and analytics solutions. 

• Guide the governance of our data products and solutions by advising and influencing business leaders and senior stakeholders with data-driven insights. 

• Partner with the data platform and infrastructure teams to manage the quality, resilient data feeds from across the enterprise. 

• Develop in-depth subject matter-expertise in understanding key strategic data sources and data lineage within the organization. 

• Scope key business challenges, identify the right data and provide direction to data analysts, data analytics product managers, data scientists, data engineers and business stakeholders. 

Qualifications: 

• Experience in data pipeline management, aggregation, and quality control. 

• Knowledge of technical controls for data collection, data quality control, and compliance. 

• Strong negotiation skills and experience in vendor management. 

• 10+ years of experience in software engineering, including 7+ years working with data engineering technologies. 

• 5+ years leading technical teams and managing complex data engineering projects and pipelines. 

• Degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field.  

• Broad expertise and experience with distributed systems, streaming systems, and data engineering tools, such as Kubernetes, Kafka, Airflow, Dagster, etc. 

• Deep knowledge of Python, SQL, database design, and master data strategies. 

• Experience defining, architecting, and rolling out data products, including ownership of data products through their entire lifecycle. 

• Experience mentoring and leading junior technical staff, incorporating modern software development tools and practices. 

• A confident peer influencer with strong communication skills who quickly establishes credibility and is capable of leading cross-functional technical teams.

Additional Qualifications (good to have): 

• Experience in the manufacturing industry or a similar domain. 

• Familiarity with handling IOT / edge device data. 

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For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export  licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls.  As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.

Job Req Type: Experienced

          

Required Travel: Yes, 10% of the time

          

Shift Type: 1st Shift/Days