Consultant

LatentView

$110K — $130K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6-10 years of relevant experience in data analytics and modeling
  • Strong proficiency in SQL with familiarity in Python or similar languages
  • Foundational understanding of data analytics infrastructure (warehousing, ETL/ELT, pipelines)
  • Experience designing data models and schemas (dimensional modeling)
  • Strong independent research and problem-solving skills
  • Excellent written and verbal communication skills for technical documentation
  • Prior experience in a data team working alongside Product Managers is advantageous

Responsibilities

  • Partner with Data Product Manager to define data requirements and technical specifications
  • Design and maintain data models for analytics and AI/ML applications
  • Conduct research on data sources and infrastructure to guide design choices
  • Evaluate AI infrastructure needs in collaboration with engineering teams
  • Document data models and lineage for team-wide consistency
  • Identify improvements in existing data infrastructure
  • Collaborate with data engineers and analysts for data quality validation

Benefits

  • Collaborative work environment with a focus on innovative projects
  • Opportunity to work with cutting-edge AI and data technologies
  • Engagement with experienced teams across product and data disciplines
  • Professional growth opportunities through exposure to various data tools and platforms
Full Job Description
Designation : Consultant

Location : San Jose, California , United States

Experience : 6 to 10 years

Job Role :

Partner closely with the Data Product Manager to translate business and product priorities into data requirements and technical specifications

Design, build, and maintain data models that support analytics, reporting, and downstream AI/ML use cases

Conduct independent research into data sources, schemas, and infrastructure options to inform design decisions

Evaluate and help shape AI infrastructure needs (e.g., data pipelines, feature stores, model-ready datasets) in collaboration with engineering

Document data models, definitions, and lineage to ensure consistency and discoverability across teams

Identify gaps or inefficiencies in existing data infrastructure and propose improvements

Collaborate with data engineers, analysts, and stakeholders to validate data quality and model accuracy

Support ad hoc analysis and prototyping to test new data model designs before full build-out

Responsibilities :

Foundational understanding of data analytics infrastructure (warehousing, ETL/ELT, pipelines, data governance)

Experience designing or contributing to data models (dimensional modeling, schema design, etc.)

Familiarity with AI/ML infrastructure concepts - how data feeds into AI systems (nice to have hands-on, but conceptual understanding is a baseline requirement)

Strong independent research and problem-solving skills - comfortable exploring ambiguous problems with minimal direction

Proficiency in SQL; familiarity with Python or similar scripting language a plus

Clear written and verbal communication, especially for documenting technical decisions for non-technical stakeholders

Prior experience working alongside a Product Manager or in a product-oriented data team is a plus

Nice to Have

Experience with cloud data platforms (Snowflake, BigQuery, Databricks, etc.)

Exposure to MLOps or AI infrastructure tooling

Background in data governance or metadata management

Required skills :

Data Modeling & AI Ops

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