Sr Data Science Engineer

San Jose, CA Austin, TX
USD 127k - 229k
Hadoop Pandas AWS Python API Keras PyTorch Spark Azure SQL Scala Machine Learning Streaming Kafka NumPy

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

Are you driven to use your expertise in data science engineering to drive the next stage of growth at Adobe? The Customer Analytics & GTM team is focused on using the power of data to deliver optimized experiences through personalization. This role will drive data engineering for large-scale data science initiatives across a wide variety of strategic projects.

As a member of the Data Science Engineering team, you will have significant responsibility to help build large scale cloud-based data and analytics platform with enterprise-wide consumers. This role is inherently multi-functional, and the ideal candidate will work across teams. The position requires ability to own things, come up with innovative solutions, try new tools, technologies, and entrepreneurial personality.

Come join us for a truly exciting career, best benefits and outstanding work life balance.

What you will do

  • Build fault tolerant, scalable, quality data pipelines using multiple cloud- based tools.
  • Deliver End to End Data Pipelines to run Machine Learning Models in a production platform.
  • Innovative solutions to help broader organization take significant actions fast and efficiently.
  • Chip in to data engineering and data science frameworks, tools, and processes.
  • Implement outstanding data operations and implement standard methodologies to use resources in an optimum way.
  • Architect data ingestion, data transformation, data consumption, data governance frameworks.
  • Help build production grade ML models and integration with operational systems.
  • This is a high visibility role for a team which is on a critical mission to stop software privacy. A lot of collaboration with global multi-functional operations teams is required to onboard the customers to use genuine software.
  • Work in a collaborative environment and contribute to the team as well as organization’s success.

What you will need

  • Bachelor’s degree in computer science or equivalent. Master’s degree is preferred.
  • 8+ years of proven track record as a data engineer.
  • 5+ years validated ability in distributed data technologies e.g., Hadoop, Hive, Presto, Spark etc.
  • 3+ years of experience with Cloud based technologies – Databricks, S3, Azure Blob Storage, Notebooks, AWS EMR, Athena, Glue etc. Familiarity and usage of different file formats in batch/streaming processing i.e., Delta/Parquet/ORC etc.
  • 2+ years’ experience with streaming data ingestion and transformation using Kafka, Kinesis etc.
  • Outstanding SQL experience. Ability to write optimized SQLs across platforms.
  • Hands-on experience in Python/PySpark/Scala and ability to manipulate data using Pandas, NumPy, Koalas etc. and using APIs to transfer data.
  • Experience working as an architect to design large scale distributed data platforms.
  • Experience with CI/CD tools i.e., GitHub, Jenkins etc.
  • Working experience with Open- source orchestration tools i.e., Apache Air Flow/ Azkaban etc.
  • Teammate with excellent communication/teamwork skills when it comes to closely working with data scientists and machine learning engineers daily.
  • Hands-on work experience with Elastic Stack (Elastic, Logstash, Kibana) and Graph Databases (neo4j, Neptune etc.) is highly desired.
  • Work experience with ML algorithms & frameworks i.e., Keras, Tensor Flow, PyTorch, XGBoost, Linear Regression, Classification, Random Forest, Clustering, mlFlow etc.

Nice to have

  • Showcase your work if you are an open - source contributor. Passion to contribute to Open-source community is highly valued.
  • Experience with Data Governance tools e.g., Collibra and Collaboration tools e.g., JIRA/ Confluence etc.

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $127,300 -- $229,300 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans.  Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

Adobe is proud to be an Equal Employment Opportunity and affirmative action employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.

Adobe aims to make accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email or call (408) 536-3015.

Adobe values a free and open marketplace for all employees and has policies in place to ensure that we do not enter into illegal agreements with other companies to not recruit or hire each other’s employees.

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