Data Engineer

Analog Devices, Inc. (NASDAQ: ) 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 FY23 and approximately 26,000 people globally working alongside 125,000 global customers, ADI ensures today's innovators stay Ahead of What's Possible. Learn more at and on .

As a Data Engineer, you will build end-to-end analytical solutions that are highly scalable, performant, secure, and resilient. You rely on sound judgement, critical thinking, and creativity to deliver customer focused data solutions that create meaningful business impact. You are experienced with various patterns of data ingestion, processing, and curation. You understand criticality of data quality, security & governance practices and are adept at it. You design solutions with strategic and long-term focus on code quality, reliability, reusability, maintainability and dataops. You are experienced in building efficient and scalable data services.

Responsibilities

Gather business and functional requirements and translate them into robust, scalable solutions aligned with Data Architecture guidelines. Perform hands-on development work on data analysis, data provisioning, data modeling, performance tuning, and optimization. Perform design and development in technologies like Fivetran, Snowflake, DBT, Python, SQL, Spark, Kubernetes, Kafka and utilize cloud technologies like Azure, AWS, and GCP. Experience working with petabyte scale structured/semi-structured/unstructured data efficiently by designing, building and maintaining robust data processing frameworks for enabling actionable insights and analytics. Create dashboards using enterprise tools such as Tableau and PowerBI. Collaborate with business stakeholders, data scientists, and analysts to understand data requirements and translate them into technical specifications. Perform root cause analysis of issues that hinder the data quality. Work with data source owner to increase quality and accuracy of the source data.

Qualifications:

• 3+ years of experience in software engineering, including 2+ years working with data engineering technologies.
• 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.
• A confident peer influencer with strong communication skills who quickly establishes credibility and is capable of leading cross-functional technical teams.

Job Req Type: Experienced

Required Travel: No

Shift Type: 1st Shift/Days