As a Data Engineer for a cutting-edge Marketing Platform, you will work on transforming and engineering data from structured and unstructured sources to drive insights and advanced analytics. The focus will be on ETL (Extract, Transform, Load) processes, utilizing Scala, Spark, and Java in a GCP (Google Cloud Platform) environment. Additionally, you'll be part of a team exploring Next Gen AI strategies, including integrating Large Language Models (LLM) into the platform. The role requires a blend of engineering and modeling skills, with a stronger emphasis on engineering.
Key Responsibilities:
- Data Extraction & Transformation: Work on ETL processes to pull data from both structured and unstructured data sources, transforming it into usable formats.
- ETL Engineering: Utilize Scala, Spark, and Java for efficient data processing and transformation within the GCP environment.
- AI Strategy Implementation: Contribute to exploring and implementing Next Gen AI strategies for the platform, including integrating LLM models.
- Data Modeling: Assist with data modeling activities to ensure optimized and scalable data storage solutions.
- Collaboration: Work closely with cross-functional teams to ensure seamless integration of data and AI features into the marketing platform.
Required Qualifications: - Data Engineering Experience: Strong experience in Data Engineering, particularly in handling structured and unstructured data.
- Scala Expertise: Expertise in Scala (must-have, not Python).
- Spark Proficiency: Hands-on experience with Spark for large-scale data processing.
- GCP Knowledge: Proficiency in working with Google Cloud Platform (GCP), including Hive tables and other cloud-native data tools.
- AI & LLM Knowledge: Familiarity with AI strategies and Large Language Models (LLM).
Preferred Qualifications: - AI Integration Experience: Experience integrating AI models into data platforms.
- Cloud Technologies: Knowledge of other cloud technologies and platforms is a plus, particularly in the GCP ecosystem.
- Data Modeling Experience: Understanding of data modeling best practices for scalable cloud-based systems.
Certifications (if any): GCP Certification or relevant certifications in AI/ML technologies are a plus but not required.
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