Lead Data Engineer / AI Native Engineer

Lead Data Engineer / AI Native Engineer

Location: Austin, TX, USA

Duration: 12 Months + Extension

Bill Rate: $90/hr on C2C

Job Type: C2C/1099 Contract

Client: To Be Discussed Later

Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Job Description:

Provide inputs for identifying best-fit architectural solutions for one or more projects; develop design of application, provide regular support/guidance to project teams on complex coding and issue resolution WITH the objective of ensuring best-fit and high quality technical solutions WITHIN the area of technology specialization and in compliance with guidelines, policies and norm.

Preferred Qualification:

• 8+ years of Data Engineering and Software Engineering experience.
• 3+ years leading complex data engineering initiatives or engineering teams.
• Proven experience building enterprise scale data platforms and pipelines.
• Experience delivering cloud native analytics and AI solutions.

Technical Skills:

• Build highly available, secure, and scalable cloud native data solutions.
• Develop ETL/ELT frameworks for ingesting, transforming, and publishing enterprise data.
• Implement high volume distributed processing using Spark and PySpark.
• Leverage GitHub Copilot, Claude Code CLI, and AI assisted development tools to accelerate engineering productivity.
• Build Proof of Concepts (POCs) and MVPs using AI powered development approaches.
• Develop cloud native solutions leveraging AWS and Databricks ecosystems.
• Build scalable architectures for data ingestion, processing, storage, and analytics.

Key Expectations:

• Strong experience in building enterprise grade data pipelines, modern Lakehouse architectures, AI enabled data products, and cloud native platforms leveraging Databricks, AWS EMR, Spark, PySpark, and AI native engineering tools such as GitHub Copilot and Claude Code.
• The role aligns with enterprise initiatives around AI assisted engineering, intelligent automation, and AI powered development workflows