Junior Data & Systems Developer

Computationaldesign; United States; In loco; USD 70.000 - 90.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health insurance

401k with company matching

Paid time off

Descrizione del lavoro

KPF in New York City is seeking a motivated Junior Data & Systems Developer to join our technology team. You will build data pipelines, manage databases, integrate APIs, and develop lightweight internal tools that support AI-enabled design workflows.

This entry‑to‑junior level role (0–4 years) offers hands‑on exposure to AI systems, large language models, and vector databases, with mentorship from an AI Systems Engineer and collaboration with architects and designers.

Competenze

• Must‑Have Python — comfortable writing scripts, automating tasks, and building small applications
• SQL — ability to write and optimize queries; experience with relational databases (MSSQL, PostgreSQL, MySQL, or SQLite)
• REST APIs — experience consuming APIs, handling JSON responses, and building simple integrations
• Flask or FastAPI — some experience building basic web applications or API endpoints
• AWS basics — familiarity with EC2, S3, and RDS; ability to deploy and manage simple cloud resources
• Docker — basic understanding of containerization and ability to build and run Docker containers
• Git — version control fundamentals; comfortable working in a collaborative codebase
• Nice‑to‑Have Experience with data pipeline tools (n8n, or similar schedulers)
• Familiarity with AWS Lambda or other serverless compute
• Basic frontend skills — HTML, CSS, JavaScript or lightweight frameworks (React, Vue)
• Exposure to data visualization tools or libraries (D3, Chart.js, etc.)
• Familiarity with CI/CD pipelines (GitHub Actions, etc.)
• Basic familiarity with LLMs and AI concepts (how data feeds into AI systems, embeddings, vector search)
• Exposure to vector databases (Azure AI Search) — even conceptual understanding is a plus
• Curiosity about AI/ML systems and eagerness to grow into more AI‑focused work
• Interest or background in AEC (Architecture, Engineering & Construction) or creative industries
• Experience working with AI coding tools like Claude Code, Cursor or GitHub Copilot

Mansioni

• Data Pipelines & Data Management: Build, maintain, and monitor ETL/ELT data pipelines to collect, transform, and load data from various internal and external sources
• Clean, validate, and structure data to ensure quality and consistency across systems
• Manage and maintain relational databases (MSSQL, PostgreSQL, MySQL, or similar), including schema design, indexing, and query optimization
• Write efficient, well‑structured SQL queries for data extraction, transformation, and reporting
• Document data flows, schemas, and pipeline logic for team reference
• API Integration: Connect to and consume third‑party and internal REST APIs to pull, sync, and process data
• Build lightweight API wrappers and integrations in Python to automate data collection workflows
• Handle authentication, pagination, rate limiting, and error handling in API integrations
• Monitor and maintain existing integrations to ensure reliability and data freshness
• Web Development & Internal Tools: Develop simple internal web applications and dashboards using Flask or FastAPI
• Build basic frontend interfaces (HTML/CSS/JavaScript or lightweight frameworks) to expose data and tools to internal users
• Collaborate with team members to understand needs and iterate on practical, easy‑to‑use tools
• Maintain and improve existing internal applications
• Cloud Deployment & Infrastructure: Deploy applications and services on AWS using core services such as EC2, S3, and RDS
• Containerize applications using Docker and manage basic container deployments
• Follow best practices for environment configuration, secrets management, and basic security
• AI Systems Support (On‑the‑Job Training & Growing Responsibility): Prepare, clean, and structure data for ingestion into AI and LLM pipelines (e.g., document chunking, metadata tagging, embedding‑ready formatting)
• Maintain and monitor vector store data ingestion pipelines (e.g., design workflows to upload data and documents, refresh indexes)
• Support the AI Systems Engineer with data tasks related to RAG (Retrieval‑Augmented Generation) systems
• Help manage knowledge bases and structured data sources that feed conversational AI tools
• Assist with testing and validating data quality within AI‑powered applications

Conoscenze

Python

SQL

REST APIs

Flask/FastAPI

AWS Basics

Docker

Git

Data pipelines

ETL/ELT

Formazione

Bachelor's degree in Computer Science or related field

Strumenti

MSSQL

PostgreSQL

MySQL

SQLite

GitHub Actions

Descrizione del lavoro

KPF is a global architecture and urban design firm known for its innovative approach to the built environment. We are committed to integrating cutting‑edge technology into our design process, and we are building an internal data and systems capability to enhance how we work, collaborate, and deliver world‑class architecture.

Role Overview

We are looking for a motivated and technically curious Junior Data & Systems Developer to join our growing technology team. In this role, you will build and maintain data pipelines, manage databases, integrate third‑party APIs, and develop lightweight internal tools and interfaces that support KPF's workflows. You will work closely with and directly support our AI Systems Engineer, helping to build and maintain the data infrastructure that powers KPF's AI systems. No prior AI experience is required, you will gain hands‑on exposure to AI systems, including large language models, retrieval‑augmented generation, and vector databases, through direct collaboration with our AI Systems Engineer. This is a role where you'll build real AI skills on the job. This is an entry‑to‑junior level role (0 – 4 years’ experience,) and we are looking for someone who is eager to learn, has foundational hands‑on experience, and is ready to grow within a collaborative and design‑forward environment. You don't need to know everything, but you need to be resourceful, dependable, and excited about building things that make a difference.

Primary Responsibilities

• Data Pipelines & Data Management: Build, maintain, and monitor ETL/ELT data pipelines to collect, transform, and load data from various internal and external sources
• Clean, validate, and structure data to ensure quality and consistency across systems
• Manage and maintain relational databases (MSSQL, PostgreSQL, MySQL, or similar), including schema design, indexing, and query optimization
• Write efficient, well‑structured SQL queries for data extraction, transformation, and reporting
• Document data flows, schemas, and pipeline logic for team reference
• API Integration: Connect to and consume third‑party and internal REST APIs to pull, sync, and process data
• Build lightweight API wrappers and integrations in Python to automate data collection workflows
• Handle authentication, pagination, rate limiting, and error handling in API integrations
• Monitor and maintain existing integrations to ensure reliability and data freshness
• Web Development & Internal Tools: Develop simple internal web applications and dashboards using Flask or FastAPI
• Build basic frontend interfaces (HTML/CSS/JavaScript or lightweight frameworks) to expose data and tools to internal users
• Collaborate with team members to understand needs and iterate on practical, easy‑to‑use tools
• Maintain and improve existing internal applications
• Cloud Deployment & Infrastructure: Deploy applications and services on AWS using core services such as EC2, S3, and RDS
• Containerize applications using Docker and manage basic container deployments
• Follow best practices for environment configuration, secrets management, and basic security
• AI Systems Support (On‑the‑Job Training & Growing Responsibility): Prepare, clean, and structure data for ingestion into AI and LLM pipelines (e.g., document chunking, metadata tagging, embedding‑ready formatting)
• Maintain and monitor vector store data ingestion pipelines (e.g., design workflows to upload data and documents, refresh indexes)
• Support the AI Systems Engineer with data tasks related to RAG (Retrieval‑Augmented Generation) systems
• Help manage knowledge bases and structured data sources that feed conversational AI tools
• Assist with testing and validating data quality within AI‑powered applications

Qualifications

• Must‑Have Python — comfortable writing scripts, automating tasks, and building small applications
• SQL — ability to write and optimize queries; experience with relational databases (MSSQL, PostgreSQL, MySQL, or SQLite)
• REST APIs — experience consuming APIs, handling JSON responses, and building simple integrations
• Flask or FastAPI — some experience building basic web applications or API endpoints
• AWS basics — familiarity with EC2, S3, and RDS; ability to deploy and manage simple cloud resources
• Docker — basic understanding of containerization and ability to build and run Docker containers
• Git — version control fundamentals; comfortable working in a collaborative codebase
• Nice‑to‑Have Experience with data pipeline tools (n8n, or similar schedulers)
• Familiarity with AWS Lambda or other serverless compute
• Basic frontend skills — HTML, CSS, JavaScript or lightweight frameworks (React, Vue)
• Exposure to data visualization tools or libraries (D3, Chart.js, etc.)
• Familiarity with CI/CD pipelines (GitHub Actions, etc.)
• Basic familiarity with LLMs and AI concepts (how data feeds into AI systems, embeddings, vector search)
• Exposure to vector databases (Azure AI Search) — even conceptual understanding is a plus
• Curiosity about AI/ML systems and eagerness to grow into more AI‑focused work
• Interest or background in AEC (Architecture, Engineering & Construction) or creative industries
• Experience working with AI coding tools like Claude Code, Cursor or GitHub Copilot

What We're Looking For in a Candidate

• Someone who takes ownership of their work and follows through from start to finish
• Comfortable working as part of a small, collaborative tech team, supporting a more senior AI engineer while owning data and infrastructure responsibilities independently
• Detail‑oriented — data quality and reliability matter; you care about getting it right
• Willing to ask questions, learn quickly, and grow with the team
• Able to communicate clearly with non‑technical colleagues (architects, designers, project managers)
• A builder mindset — you enjoy creating tools that solve real problems for real people

Education

• Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field — or equivalent practical experience
• Relevant certifications (AWS Cloud Practitioner, AWS Developer, etc.) are a plus but not required

Work Environment

• This position requires you to be in person in our New York office 5 days per week.

Pay Range

$70,000.00 - $90,000.00 Annual

Why KPF?

KPF’s mission is to elevate cities through impactful design, collaborating closely with the world’s most forward‑thinking clients to create high performing, carefully crafted buildings that are unique to their physical, social, and environmental contexts.

Career Growth

Opportunities for training, development, and career progression.

Company Culture

Collaborative, high‑performance environment with a focus on innovation and excellence.

Benefits

• Comprehensive health insurance, including medical, dental, and vision insurance
• 401k with company matching contributions
• Paid time off and other perks

KPF is an equal opportunity employer.