Senior Data Engineer, Fraud
San Jose
hace 5 días

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone from emerging artists to global brands everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.

We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity

Adobe Legal Fraud team is looking for a full time Data Engineer with experience in building data integrations on Hadoop and cloud solutions like AWS, Azure technology stack.

The ideal candidate will have a passion for simplifying and automating workflows, for making things better, for being efficient and helping the team do more with less, who are self-motivated to push themselves in a team oriented culture.

What you'll Do

Build big data pipelines and structures that power fraud predictive models and intelligence services on large scale data sets.

Drive and deliver on the infrastructure focusing on Engineering best practices and efficiency with defined measurable critical metrics.

Implement and manage large scale ETL jobs on Hadoop / Spark clusters.

Delivery Oversight, Tech oversight - mentorship, reviews, modernization.

Effectively communicate status, issues, and risks in a precise and timely manner

What you need to succeed

Bachelor’s degree preferably in engineering, computer science, mathematics, information systems, data analysis

10+ years of data engineering experience

Deep Technical proficiency in SQL, Python

Experience in data processing using traditional and distributed systems (e.g., Hadoop, Spark, Airflow).

Experience crafting data models and data warehouses and using SQL and NoSQL database management systems.

Able to identify the root cause of problems and identify, propose, and recommend innovative solutions

Ability to scale, automate, and improve data processes to streamline efficiencies

Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources.

Experience in large scale distributed data processing.

Good knowledge or experience with cloud technologies, Graph DB, Mongo DB

Experience with graph data models and graph languages (Cypher, Gremlin) would be a plus

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