We seek an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives.
Key Responsibilities:
Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems.
Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT.
Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions.
Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows.
Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode.
Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit.
Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg.
Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving.
Requirements: Required Qualifications
5+ years of experience with advanced data modeling techniques and concepts (e.g., Facts, Dimensions, Partitions).
5+ years of experience designing and implementing end-to-end data ingestion and ETL processes within Data Lakehouse architectures.
5+ years of hands-on experience programming in SQL and Python, PySpark, Java, or Scala.
Demonstrated experience leading technical projects, driving stakeholder alignment, and navigating cross-functional dynamics.
Proven experience working within cloud environments (AWS or GCP), with a strong requirement for AWS.
Deep understanding of the modern data landscape and open-source tools (e.g., Iceberg, DBT, Airflow).
Proven capability in using and orchestrating Gen-AI workflows based on CloudCode and Cursor.
Preferred Qualifications:
Deep expertise in the AWS ecosystem, including Glue, Athena, SageMaker, and EMR.
Advanced experience with Data Warehouse technologies, especially Apache Iceberg or BigQuery.
Leadership or mentorship experience within a data engineering or analytics unit.
Background or domain knowledge in cybersecurity is a strong advantage.
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This position is open to all candidates.