CoComply AI

CoComply provides a flexible SaaS platform for data and AI governance, enabling organizations to certify their critical assets through a four-step process. The platform addresses the challenges of traditional governance by offering a self-serve product that enhances compliance efficiency and reduces risks associated with data management. With over 4,000 startups trusting their solution, CoComply positions itself as a cost-effective alternative to complex enterprise-grade tools, delivering significant ROI and productivity gains. Their approach simplifies the certification process, making it accessible for businesses of all sizes, while fostering a partnership ecosystem to unlock the transformative potential of data.

AI CertificationComplianceData GovernanceProductivity GainRegulatory Intelligencecocomply.ai

CoComply AI

AI CertificationComplianceData GovernanceProductivity GainRegulatory Intelligencecocomply.ai

HQKanab, US

Team Size2

Open Jobs3

Total Funding-

Latest Fundraise2 years ago

Join the Team

Data & AI Governance Intern - (Governance & Certification Focus)

RemoteIN

Remote • IN

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Contract • Belgrade, RS

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Internship • Manchester, GB

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ContractRotterdam, NL

Contract • Rotterdam, NL

Location: Remote

Duration: 8–12 weeks (with extension potential)

Level: Advanced graduate student or early-career engineer

Internship Type: Paid, full-time

Role Overview

We’re looking for a technically strong intern to support the design, implementation, and automation of data and AI governance controls across real-world enterprise environments. This role sits at the intersection of data engineering, analytics, and governance execution—not policy writing.

You’ll work directly on live assets such as reports, pipelines, and metadata to help inventory, map, validate, and certify critical data assets used by regulated enterprises.

What You’ll Work On

Analyze Tier 1 / Tier 2 reports and dashboards to identify underlying data elements
Perform attribute-level mapping between reports, source systems, and canonical data models (CDMs)
Support data lineage documentation (source → transformation → report)
Assist with data quality rule definition and validation
Help automate evidence generation for audit and regulatory reviews
Use SQL / Python to profile data and flag gaps or anomalies
Contribute to internal tooling or scripts that reduce manual governance effort

Required Skills

Strong SQL (joins, aggregations, window functions)
Working knowledge of Python or another scripting language
Familiarity with data warehouses (Snowflake, BigQuery, Redshift, Databricks, etc.)
Ability to read and interpret report logic and data schemas
Comfort working with imperfect, real-world enterprise data

Nice to Have

Exposure to data governance, data quality, or metadata tools
Understanding of financial or regulatory reporting
Experience with Git, YAML, or CI/CD workflows
Familiarity with dimensional models or canonical data models

What You’ll Learn

How governance actually works in practice (not slide decks)
How regulatory expectations translate into technical controls
How certified data assets are built, validated, and defended
How to work inside enterprise-scale data environments.