Consequential builds for practitioners who own their work.

Common Works builds with a curated mix of full-time team members and a Talent Network of engineers, product leaders, and operators. You embed in real businesses, work alongside management, and ship the systems and products that move EBITDA.

For practitioners who take outcomes seriously.

The best practitioners don’t want bench time or fabricated urgency; they want hard problems with real stakes. Every Common Works engagement is that: embedded inside a business, working alongside operators who are accountable for results.

You work with people who’ve done this at serious firms, on real problems. The team is curated and the work is selective, because the only thing that matters is what gets shipped and what it’s worth.

Capable

We take the work seriously. Every engagement is a chance to demonstrate that applied AI creates real, measurable business value, not a chance to produce deliverables that look good in a deck.

Practical

We ship. Clarity over cleverness, working software over architectural elegance, outcomes over process. The measure of a good engagement is what remains and what it’s worth.

Collaborative

We work alongside operators, not above them. The best outcomes come from people who listen well, communicate clearly, and earn trust inside the businesses they’re embedded in.

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Engineering

Forward-Deployed Engineer

NY / Remote

Data & AI Solutions Architect

NY / Remote

AI / ML Engineer

NY / Remote

Data Engineer

NY / Remote
Advisory & Delivery

Forward-Deployed Product Manager

NY / Remote

Client Engagement Manager

NY / Remote

AI Value Creation Consultant

NY / Remote

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Data Engineer

NY / Remote

Stand up the data and systems integration that AI value creation depends on.

About Common Works

Common Works is an AI-native services firm built for private equity. We work at the intersection of investment diligence and technical delivery, helping PE sponsors and their portfolio companies translate AI from a thesis into operating outcomes: higher EBITDA, better margin, and durable capability inside the business.

Our model isn’t consulting. We are builders who understand how deals work, and deal practitioners who can ship AI transformations. We forward deploy engineers, architects, and operators inside portfolio companies, work alongside management, and are accountable for the outcome.

The Role

Data Engineers at Common Works build the data foundations that AI value creation depends on. Before a model can surface insight or an agent can complete a task, the data must be trustworthy, connected, and accessible. At many companies we work with, it isn’t yet. You are the person who changes that, under engagement timelines that don’t allow for multi-quarter data projects.

The work spans integration, transformation, and infrastructure. You will connect disparate source systems, normalize messy operational data, build pipelines that AI engineers can actually rely on, and put observability in place that makes those pipelines maintainable after the engagement closes.

Key Responsibilities
  • Build and maintain data pipelines integrating across portfolio company source systems: ERP, CRM, financial systems, operational databases
  • Design and implement data models and transformation layers that make data trustworthy and ready for downstream AI use
  • Establish data quality checks, observability, and alerting for critical pipeline dependencies
  • Work closely with AI/ML engineers to understand upstream requirements and support downstream use cases
  • Document data lineage, schema decisions, and pipeline architecture as handoff artifacts
  • Move fast while building systems that are maintainable by the portfolio company team after the engagement closes
Qualifications

Required

  • 4+ years of data engineering experience with a track record of production pipeline delivery
  • Strong SQL proficiency and experience with at least one Python-based orchestration or transformation framework (dbt, Airflow, Prefect, or similar)
  • Comfort working with legacy systems (on-premise databases, older ERP platforms, non-standard APIs) where the data lives but the infrastructure isn’t clean
  • Experience building integrations with enterprise source systems and third-party APIs
  • Familiarity with modern cloud data warehousing: Snowflake, BigQuery, Databricks, or equivalent
  • Understanding of data quality patterns, schema evolution, and pipeline reliability

Preferred

  • Experience building data infrastructure specifically for AI/ML model input or inference pipelines
  • Background in multi-client consulting or PE portfolio company environments
  • Experience with data observability tooling (Monte Carlo, Great Expectations, Elementary, or similar)

Join us.

Tell us who you are and what you’ve shipped.

Contact

Work location & eligibility

Country
City / location
  • Talent Network positions require authorization to provide independent-contractor services from your location.
  • Full-time positions require employment authorization.
  • Common Works is not currently able to sponsor visas.

Your application

Upload your resume
PDF or DOCX · drag & drop or browse

By applying you consent to Common Works contacting you about opportunities. Your application, including your resume, is handled as described in our Privacy Policy.