Big Data Architect with AI–Day 1 onsite Seattle, WA

AI Big DATA Architect

Location: North America (Seattle)

Type of Employment: contract

2. Key Result Areas and Activities:

• Seeking a Data Engineer with 13+ 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:

• 6-8 years as Data Engineer
• 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