Senior Data Engineer with Data Science (AWS) (AI)

Position: Senior Data Engineer with Data Science

Location: North America (Seattle)

Purpose of the Position: Senior Data Engineer to help design and implement cloud services for their
Data Science platform, ensuring a streamlined experience for data scientists and engineers.
This position demands technical expertise, and hands-on leadership to drive innovation in
enterprise-scale data infrastructure. Collaboration with Applied Scientists, Knowledge Engineers
within the Data Governance Team, and Data Engineering in the AI Platform team is essential.
Additionally, the Senior Engineer will work closely with InfoSec and Security teams to ensure secure
and seamless integration and coordinate with engineering leadership to manage technical risk and
deliver critical features on time.
Accelerate the development and fine-tuning of Agentic AI models to improve their capabilities and
performance. In parallel, implement vertical benchmarking programs like EDGE to create strict
evaluation criteria and enable comparison of various AI models and applications. Empower PXE
Engineers to increase AI productivity and act as a force multiplier

2. Key Result Areas and Activities:
Seeking a Data Engineer with 10+ years of hands-on data architecture experience designing
and managing large-scale data lakes and warehouses.
Solid understanding and hands-on experience with Apache Iceberg and AWS Glue
Deep experience with AWS systems like Lakeformation, IAM and Redshift.
Proficiency in Python, Scala, or Java for ETL and custom tooling is essential.
Proven expertise in complex schema and ERD design, maintaining data dictionaries, and
developing real-time/batch data pipelines using tools like Kafka, Spark, or similar.
AI/ML integration familiarity, leadership abilities, and strong problem-solving skills
3. Work and Technical Experience:
Essential Skills:
Big Data Technologies
AWS experience AWS Glue, Redshift, SageMaker
Databricks
Snowflake

Building large pipelines
Experience in data and ML lifecycle
Include architectural leadership, data modeling, building real-time data pipelines,
implementing data governance, optimizing performance, and enabling AI/ML workflows.

Desirable Skills:
Data Governance: Hands-on experience with implementing data governance frameworks,
compliance, and security standards.
Leadership: Demonstrated ability to lead teams, mentor junior engineers, and work in cross-
functional environments.
Experience with vector databases/RAG, petabyte-scale data, advanced analytics tools, and
industry experience in AI/ML, SaaS, or cloud technology

4. Qualifications:
10+ years as Data Architect
Bachelor s degree in computer science, software engineering, or related field (Master's
degree is a plus)
Demonstrates continued learning through one or more technical certifications or related
methods

5. Qualities:
Self-motivated and focused on delivering outcomes for a fast-growing team and firm
Able to communicate persuasively through speaking, writing, and client presentations
Work independently based on the mentorship provided by managers
Demonstrates problem solving, multi-tasking, troubleshooting skills with a high degree of
flexibility
Able to work with teams and clients in different time zones
Proven learning agility as technologies and capabilities evolve rapidly
Strong analytical, troubleshooting, and problem-solving skills.
Research focused mindset