Collaborate with Data Architects, Operational Architects, and Data Analysts to understand the data and operational requirements across different business units.
Partner with data owners to ensure seamless, reliable data ingestion for both traditional analytics and GenAI-powered applications.
Master "Vibe Coding" and AI-orchestrated development to accelerate the delivery of new data pipelines and GenAI applications, reducing the end-to-end development lifecycle from days to hours.
Develop and implement data transformations to enrich and provision data, following established specifications and standards while utilizing AI-first workflows.
Design and implement robust system architectures for real-time, near real-time, and batch processing data flows to meet the operational demands of complex business systems.
Design and deploy GenAI-powered "Self-Service" tools, including automated documentation generators and natural language interfaces, to empower business users and reduce routine engineering requests.
Implement monitoring and CI/CD automation processes to track data quality and ensure the reliability of AI-supported data services.
Standardize AI-first engineering workflows across the team to ensure high-quality, auto-validated, and well-documented code delivery.

5+ years of experience as a Data Engineer
Proven experience with AI-first approaches and "Vibe Coding," with a demonstrated ability to deliver production-ready data pipelines using AI orchestration rather than purely manual coding
Deep proficiency with AI-assisted coding tools, including Cursor, GitHub Copilot, or Gemini, to modernize and accelerate engineering workflows
Solid skills in System Design for diverse data architectures, including expert-level knowledge of batch processing and real-time/streaming processing
Proficient in coding with Python (primary) and SQL, with experience in ETL and data processing
Hands-on experience with Distributed Systems and Big Data technologies, including Spark and the Hadoop ecosystem (Hive, Impala, Kafka)
Proven proficiency in Data Modeling using industry best practices (e.g., Kimball, Inmon) to ensure data integrity
Ability to monitor critical data pipelines for quality and resolve any issues effectively
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field or equivalent experience
Strong communication skills, both written and verbal.

Senior Data Engineer

Key skills