Forward Deployed Engineer

Title: Forward Deployed Engineer - Arkham Technologies

URL Source: https://apply.workable.com/j/B927AF1B70

Markdown Content: Forward Deployed Engineer

About Arkham:

Arkhamis a Data & AI platform that helps large enterprises:

• Unify fragmented systems and data
• Build a single source of trusted operational metrics
• Solve complex challenges with AI tailored to their operations

Teams at **Circle K and Kimberly-Clark **partner with us to deploy AI-powered solutions for sell-out forecasting, pricing and promo analysis, and automated order assignment. With Arkham, they achieve high-impact results fast, creating a strong foundation for long-term AI transformation.

Know more about Arkham:

• Our website
• Youtube Channel
• Medium blog

About the Role

Our implementation model is built around two core roles:

• Forward Deployed Engineer
• Forward Deployed Data Scientist

As a **Forward Engineer **, you'll be the technical bridge between Arkham's Data Sync platform and our clients. Your primary focus is building the connectors that make data flow — REST APIs & JDBC/ODBC, — using frameworks like dlt, Airbyte, and Meltano (desired but not mandatory). But unlike a purely internal engineering role, you'll own the full implementation cycle: working directly with client teams to understand their data landscape, then building and deploying the connectors that unlock it.

You'll manage 3-4 client implementations at a time, moving fast from discovery to production while keeping your connector work reusable and scalable across engagements.

What You’ll Work On

Build and Own Data Connectors

• Design and implement connectors for diverse data sources including:
• REST APIs
• JDBC / ODBC databases
• Flat files and object storage
• Custom ingestion scripts

Every connector should prioritize **reusability, configurability, and scalability **.

Lead Client Implementations End-to-End

Own the data integration process from initial discovery to production deployment.

This includes:

• Understanding the client’s data architecture
• Defining integration requirements
• Building connectors
• Deploying them into Arkham’s platform

Most integrations are expected to reach production within 2–4 weeks.

Design Robust Integration Architecture

Create adapter and abstraction layers that standardize how connectors handle:

• Authentication mechanisms
• Pagination and incremental syncs
• Rate limits
• Error handling and retries
• Schema normalization

Your goal is to ensure connectors behave consistently across systems.

Work Directly With Client Technical Teams

Collaborate with engineering and data teams to:

• Understand source systems
• Map and validate data flows
• Ensure outputs align with business requirements

You’ll translate real-world operational systems into **clean, reliable data pipelines **.

Build Analytics-Ready Data Pipelines

Write clean SQL and design transformations that produce **high-quality datasets ready for analytics and AI workflows **.

Your pipelines should be:

• Correct
• Observable
• Maintainable
• Scalable

Improve the Connector Library

Each integration should strengthen Arkham’s platform.

You’ll contribute reusable patterns and improvements back to the shared connector framework so that **every engagement accelerates the next one **.

What We Require

Experience

• 2+ years of backend or data engineering experience
• Strong Python programming skills
• Hands-on experience building REST API integrations
• Solid SQL and relational database fundamentals

Communication & Ownership

You should be comfortable:

• Explaining technical work to technical and non-technical stakeholders
• Working in client-facing environments
• Owning integrations from problem definition to production

This role requires engineers who **take responsibility for outcomes **, not just code.

Technical Environment

Experience with cloud environments is expected.

Preferred:

• AWS

Bonus Skills

Nice-to-have experience includes:

• CI/CD applied to data workflows
• Data observability and testing frameworks
• Familiarity with AI-driven analytics and Generative AI use cases
• Experience with data integration frameworks such as:

*   **dlt**

*   **Airbyte**
*   **Meltano**