Data Engineer-Adobe Exp Platform

Responsibilities

• Engage with team counterparts to explore and deploy technologies for creating data sets using a combination of batch and streaming transformation processes.
• Support the development of solutions in an end-to-end framework on a group of core data technologies.
• Contribute to the evaluation, research, and experimentation efforts with batch and streaming data engineering technologies in a lab.
• Collaborate with data engineering related groups to inform on and showcase capabilities of emerging technologies and enable their adoption.
• Contribute to the definition and refinement of processes and procedures for the data engineering practice.
• Work closely with data scientists, data architects, ETL developers, other IT counterparts, and business partners to identify, capture, collect, and format data from various sources.
• Develop, code, test, deploy, monitor, document, and troubleshoot scalable analytic data systems including automation for deployment and monitoring.

Qualifications

• Experience with Adobe solutions (ideally Adobe Experience Platform, XDM, RTCDP DTM/Launch) and REST APIs.
• Digital technology solutions (DMPs, CDPs, Tag Management Platforms, Cross-Device Tracking, SDKs, etc.).
• Knowledge of Real Time-CDP and Journey Analytics solution.
• SQL experience: querying data and sharing insights.
• Experience with Agile development / SAFe, Scrum, and Application Lifecycle Management.
• Experience with ingesting various source data formats such as JSON, Parquet, SequenceFile, Cloud Databases, MQ, Relational Databases such as Oracle.
• Experience with Cloud technologies (such as Azure, AWS, GCP) and native toolsets.
• Understanding of cloud computing technologies, business drivers, and emerging computing trends.
• Thorough understanding of Hybrid Cloud Computing: virtualization technologies, Infrastructure as a Service, Platform as a Service, and Software as a Service Cloud delivery models and the current competitive landscape.
• Experience with processing large data sets using Hadoop, HDFS, Spark, Kafka, Flume or similar distributed systems.
• Experience with NoSQL data stores such as CosmosDB, MongoDB, Cassandra, Redis, Riak or other technologies that embed NoSQL with search such as MarkLogic or Lily Enterprise.
• Creating and maintaining ETL processes.
• Troubleshoot complex problems and work across teams to meet commitments.
• Excellent computer skills and proficiency in digital data collection.
• Ability to work in an Agile/Scrum team environment.
• Strong interpersonal, verbal, and writing skills.
• Understanding of big data platforms and architectures, data stream processing pipeline/platform, data lake and data lake houses.
• Understanding of cloud solutions such as Google Cloud Platform, Microsoft Azure & Amazon AWS cloud architecture & services.
• Familiarity with AI assisted research, summarization, and content generation.
• Understanding of responsible AI use, including ethics and data protection.
• Strong in the use of Microsoft Office software, data querying platforms (Databricks is a plus) and statistical programming tools such as Python.

What We Offer

• Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.
• Our Culture: An environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging.
• Compensation: Competitive pay and bonus eligibility.
• Work Life Balance: Flexible hybrid work environment, 2-days a week in our Las Colinas/Irving, TX office.