We are combining data, programmatic decisioning, and real-time delivery to build Customer Data Platforms (CDPs), complimented by a suite of client-specific managed services.
Adobe Experience Platform, is powerful, flexible, open system for bulding and managing complete solutions that drive customer experience. Experience platform enables organizations to centralize and standardize customer data and content from any system and apply data science and machine learning to deliver consistent interactions at scale across several orchestration layers within any marketing stack.
Our engineering team is responsible for building the Adobe Experience Platform. We help thousands of customers collect, manage and synthesize petabytes of data with high fidelity and velocity. We help them make sense of that data, glean insights and run algorithms, so they can deliver delightful experiences in real-time, every time. If building new secure micro-services in the cloud based on open-source technologies at large-scale is something that might interest you, lets share some thoughts, we would like to meet!
Work you’ll do
We rely on powerfully insightful data to inform our systems and solutions—and we’re seeking an experienced pipeline-centric Data Engineer to put it to use. Our ideal hire will have the mathematical and statistical expertise you’d expect, combined with a rare curiosity and creativity. You’ll wear many hats in this role, but much of your focus will be building out our Python ETL processes and writing superb SQL. Beyond technical prowess, you’ll need the soft skills it takes to communicate highly complex data trends to organizational leaders in a way that’s easy to understand. We’re looking for someone willing to jump right in to help the company get the most out of our data.
Your responsibilities will include:
- Analyze customer use case, available data to prepare for automated & ongoing data ingestion to meet customer requirements
- Design technical solution with all data ingestion, transformation & scheduling to review & sign-off with customer
- Identifying AEP enhancements, extending frameworks and incorporating new ideas
- Closely collaborating with other AEP team members (sales teams, engineers, consultants) and onshore teams for delivering projects
- Optimize data pipelines, queries, and workflows for performance, scalability, and reliability, identifying and resolving bottlenecks as needed.
- Collaborate with cross-functional teams, including marketing, IT, and analytics teams, to understand business requirements, define data requirements, and deliver solutions that meet business needs.
- Document data engineering processes, workflows, and best practices. Provide training and support to internal teams on AEP CDP data management and usage.
- Building/operating highly scalable, fault tolerant, distributed systems for extraction, ingestion to process large data sets
- Experience with data analysis, modeling and mapping to coordinate closely with Data Architect(s)
- Build the necessary schemas, workflows to ingest customers data into AEP successfully
- Create necessary identity namespaces, privacy settings and merge poilicys required to build the solution
- Build Audiences (segmentations) and create necessary pipeline for Destination activation
- Post-Deployment, provide ongoing maintenance & support of solution & knowledge transfer to offshore support team
Our team
You’ll join a team of passionate. As an engineer in digital marketing and digital media, you’ll get an unprecedented opportunity to work at the intersection of creative content, data science, and experience delivery. If you’re intellectually curious, hardworking and solution-oriented, you’ll fit right into our fast-paced, collaborative environment. In addition to working daily with our DataScience Team and DevOps Team to deliver production-level pipelines that will run unattended for weeks and months. you’ll also work closely with our Project Management Team to understand our clients’ needs and any change requests that drive our development efforts.
Qualifications
Required:
· Bachelor's degree in Computer Science, Engineering, or related field.
· Proven experience (X years) working as a Data Engineer or similar role, with expertise in data engineering, data architecture, and data management.
· Strong knowledge of Adobe Experience Platform (AEP) and its Customer Data Platform (CDP) capabilities, including data modeling, segmentation, and activation.
· Proficiency in data integration technologies and tools such as Apache Kafka, Apache Nifi, or Talend.
· Experience with cloud-based data platforms and services such as Adobe Experience Cloud, AWS, or Azure is a plus
· Programming skills in languages such as Python, SQL, or Scala is a plus
· Experience with big data technologies such as Hadoop, Spark, or Hive is a plus.
· Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
· Adobe Experience Platform Architect certification or relevant professional certifications are a plus.
· Follows data development best practices, and enjoy helping others learn to do the same.
· An independent thinker who considers the operating context of what he/she is developing.
· Believes that the best data pipelines run unattended for weeks and months on end.
· Familiar with version control, you believe that code reviews help to catch bugs, improves code base and spread knowledge.
· Ability to travel 5-10% of the time
Helpful, but not required:
· Knowledge in:
o Experience with large consumer data sets used in performance marketing is a major advantage.
o Familiarity with machine learning libraries is a plus
o Well-versed in (or contributes to) data-centric open source projects.
o Reads Hacker News, blogs, or stays on top of emerging tools in some other way
o Data visualization
o Experience with stream-processing systems: Apache Spark-Streaming, Apache Storm etc.
o Experience working in open table / in-memory table formats for huge analytics dataset: Iceberg, Parquet, Arrow, AVRO etc.
· Adobe Qualified – Adobe Experience Platform (AEP) Certification
· Technologies of Interest:
o Languages/Libraries – Python, Java, Scala, Spark, Kafka, Hadoop, HDFS, Parquet.
o Cloud – AWS, Azure, Google