Technical Consultant

YO AI Labs

  • New Jersey, New Jersey
  • 9 days ago

    Highlights

    Strong experience with Databricks, DBT Core or Cloud, Python, Spark, SQL, distributed compute paradigms including in-memory, distributed, and MPP architectures, and Data Vault 2.0 including automate_dvDeep knowledge of AWS services including S3, Glue, Redshift, EMR, DynamoDB, Lambda, Athena, and Kinesis. Role Overview: The Technical Consultant role is responsible for end-to-end client management, program management, business growth, and client success by ensuring solutions are scalable, secure, cost-efficient, and aligned with modern data engineering, analytics, and AI/ML best practices.

    Numbers & Facts

    LocationNew Jersey, New Jersey

    Description

    Role Name : Technical Consultant, Pharma (Business Translator) 

    Location : New Jersey, USA

    Experience: 10 -15 Years

    Role Overview: The Technical Consultant role is responsible for end-to-end client management, program management, business growth, and client success by ensuring solutions are scalable, secure, cost-efficient, and aligned with modern data engineering, analytics, and AI/ML best practices. The consultant will partner with engineering teams, data product owners, and business stakeholders to establish architectural standards, design cloud-native data platforms, and guide technical execution across complex programs.

    Roles and Responsibilities:

    • Drive senior client workshops, problem framing, and solution framing
    • Lead end-to-end client advisory, opportunity creation, and demand generation
    • Engage with business and technical teams to align architecture with business requirements
    • Support RFP and RFI responses and architectural evaluations
    • Experience with Life Sciences datasets, migration, and modernization
    • Understanding of operational layers L1, L2, and L3, along with ontology and context layers
    • Define and enforce data modeling, metadata, lineage, and quality standards
    • Implement CI/CD pipelines and monitoring frameworks
    • Ensure architectures support observability, reliability, and operational excellence
    • Architect end-to-end solutions on AWS and Databricks
    • Define architectural standards, patterns, and best practices
    • Review and guide solution designs for scalability, performance, and security
    • Evaluate technology options and recommend long-term architectural strategies
    • Translate business and analytical requirements into scalable data models
    • Assess current-state data architectures and define future-state models
    • Design scalable data models for analytical and operational workloads
    • Demonstrate strong understanding of metadata, lineage, data quality, and governance frameworks
    • Be familiar with distributed compute paradigms and cloud-native modeling patterns

    Required Qualifications:

    • At least 10+ years of experience in AI, software development, data engineering, or data architecture along with 
    • 5+ years of Life Sciences consulting experience
    • Experience driving modernization initiatives for AI products with AI foundations, governance, operational layers, and context layers
    • Strong experience with Databricks, DBT Core or Cloud, Python, Spark, SQL, distributed compute paradigms including in-memory, distributed, and MPP architectures, and Data Vault 2.0 including automate_dvDeep knowledge of AWS services including S3, Glue, Redshift, EMR, DynamoDB, Lambda, Athena, and Kinesis
    • Experience leading architecture across multi-team onsite and offshore delivery models
    • Executive presence to lead VP and Executive Director-level meetings and steering committees independently
    • Ability to drive thought leadership, technical visioning, workshops, and client success initiatives
    • Life Sciences experience preferred
    • Ability to translate complex analytical requirements into scalable architectures including data models, ETL pipelines, and consumption layers
    • Experience designing and deploying dashboards and self-service analytics on relational and non-relational databases
    • Strong understanding of CI/CD, DevOps, static code analysis, and test-driven development
    • Experience with cloud migration patterns and modern data platform design
    • Experience defining data standards, metadata models, lineage, quality rules, and governance patterns
    • Experience implementing logging, monitoring, observability, and cost optimization frameworks
    • Experience driving enterprise data platform adoption and modern data practices

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