Data Engineering Lead (mAI Data Foundation Core)

We provide Recruitment and Staffing services to many industries and domain through our innovative and customized solutions and passionate commitment to research. Ability to understand the hiring strategies, availability of talent and compensation benchmarking makes us proud hiring partner for various industries. We work as trusted business partners and always strive to deliver the most value and highest return on investment for our clients. We are highly trained business professionals with strong understanding of clients need. We work closely with the leading staffing trade associations, training, and research organizations to ensure we are knowledgeable of thustry trends and technologies.

Required Skills

• AWS: S3, Glue, Lambda, Athena, Redshift, EMR, Lake Formation, Step Functions, EventBridge, API Gateway, IAM
• Python, PySpark, SQL
• Apache Spark, Kafka (preferred)
• Data Lake/Lakehouse architecture
• Data Governance, Metadata, Lineage, Data Quality
• GenAI, RAG, Vector Databases, Knowledge Graphs
• Terraform, GitHub, CI/CD
• Excellent stakeholder management and communication.

Key Responsibilities

• Lead the architecture and implementation of AWS-based structured and unstructured data platforms supporting AI and GenAI solutions.
• Design scalable data ingestion pipelines, data models, metadata, lineage, data quality, and governance frameworks.
• Establish reusable data contracts, integration patterns, and secure data access across enterprise AI products.
• Collaborate with Takeda Enterprise Architecture, Data Engineering, AI, Security, and Product teams to define the Data Foundation roadmap.
• Drive engineering standards, technical reviews, backlog prioritization, and mentor distributed engineering teams.

Regards,

Mohammed ilyas,

PH +1 229-264-4024 or Text - 229-469-1455 or you can share the updated resume at Mohammed@vtekis. com

All your information will be kept confidential according to EEO guidelines.