About the Role

We are hiring two Full-Stack Developers, Data Applications, who will develop the backend data pipelines and self-service application layer.

The developers will work across the same surface: Python pipelines, Snowflake workflows, REST API integrations, and web-based self-service applications that replace 40+ Alteryx Gallery apps used daily by five internal teams.

Our team operates in an AI-assisted development model. We use Claude (Anthropic) as an active co-author across the full engineering lifecycle, code generation, agentic task execution, architectural review, and documentation. This is not optional tooling. It is how we move fast with a lean team against a hard deadline.

How We Work — AI-Assisted Engineering

This team builds with AI, not alongside it.

We use Claude (Anthropic) as an active co-author across the full development lifecycle, prompt-driven code generation, agentic task execution via Claude Code, UI scaffolding, test generation, and documentation. This is not optional tooling. It is how we compress delivery timelines and maintain quality with a lean team against a hard December deadline.

We are looking for engineers who have already worked this way — who know how to write precise prompts, decompose complex tasks for agentic execution, validate AI-generated code critically, and iterate quickly when outputs miss the mark. Prior experience shipping production code using AI-assisted workflows is a meaningful differentiator, not a nice-to-have.

What You'll Own

Backend Pipeline Migration

Rebuild 22 shared Alteryx macros as a versioned Python shared library — Git-controlled, unit-tested, and importable across all new scripts — using Claude Code for accelerated generation and review
Migrate scheduled data pipelines (daily, weekly, monthly) to Python on the existing AWS orchestration infrastructure, with Slack-based failure notifications replacing Alteryx Server alerts
Replicate all Snowflake read/write workflows currently executed via Alteryx, including deduplication, standardization, and enrichment pipelines — ensuring all writes are idempotent and auditable
Build replacement logic for the full Data Ingestion, Data Update, Data Pull, and Data Count Pull operational task set
Own credential management migration from Alteryx Server to AWS Secrets Manager or Parameter Store

REST API Integrations

Rebuild connectors for CoreSignal Contact Enrichment, PredictLeads (Companies and Technology Lookup), Lastbounce (file upload and result retrieval), and the Jira Iterative connector
Implement OAuth2 flows, pagination handling, and JSON parsing in Python across all external API integrations
Rebuild Jira Ticket Breakdown and Data Research Ticket Breakdown outputs using the Jira REST API

Scheduled Reporting

Generate Excel output files (openpyxl / xlsxwriter) and push to SharePoint via Microsoft Graph API for all 10+ weekly and monthly reports currently delivered to the Data Ops SharePoint site
Build and maintain the Prod-to-Stage DB Sync and Server metadata update pipelines

Self-Service Application Layer

Rebuild 40+ Alteryx Gallery applications as Python-backed web apps (Flask or FastAPI backends, Next.js/react— starting with EFO Data Pull variants, Quotes App, Look-a-Like apps, and Data Research validation tools
Build parameterized interfaces (dropdowns, file uploads, filter inputs) that match current Alteryx app behavior without requiring users to understand the underlying logic
Ensure all app outputs — Excel files, CSV exports, SharePoint uploads, email notifications — are delivered the same way users expect today
Implement role-based access control for the self-service layer, controlling which users and teams can access which applications
Own the hosting and deployment model (internal server, S3 static + Lambda, or containerized) in collaboration with the broader engineering team

Agentic Development Workflows

Structure and direct Claude Code sessions to autonomously scaffold application components — backends, form logic, output handlers — maintaining code quality through rigorous review
Develop reusable prompt templates and task decomposition patterns that accelerate delivery as the migration progresses
Validate and harden AI-generated code against production requirements before deployment

Required

5+ years of Python development — pandas, requests, openpyxl, regex as daily tools
Solid Snowflake SQL — joins, CTEs, window functions, write operations (INSERT, MERGE, TRUNCATE/INSERT)
REST API experience — OAuth2, pagination, rate limiting, JSON/XML parsing
Full-stack capability — Python backend (Flask or FastAPI) with HTML/JS frontend; able to build and ship a working web application end to end
AWS fundamentals — S3 read/write, Lambda or EC2 execution, Secrets Manager or Parameter Store
Demonstrated experience with AI-assisted development — using LLMs (Claude, Copilot, GPT-4, or equivalent) as active co-authors in a production engineering context, not just for autocomplete
Hands-on experience with agentic coding tools — Claude Code, Cursor, Devin, or similar — directing autonomous AI execution for real deliverables
Comfort working from existing workflow documentation to rebuild logic in a new stack
Git proficiency — branching, PRs, versioned releases

Strong Plus

Microsoft Graph API — SharePoint file writes, list operations, and email dispatch
Experience building self-service data tools or internal ops tooling for non-technical users
Familiarity with Alteryx Designer (understanding what you're replacing is a meaningful head start)
Workflow orchestration tools — Airflow, Prefect, Step Functions, or similar
React or Vue for more complex frontend components
KNIME Analytics Platform familiarity — relevant for the analyst self-service tool decision
Data quality libraries — Great Expectations, phonenumbers, email-validator
Experience decomposing complex engineering problems into prompt sequences for agentic AI execution

2 Jobs im Bereich Great expectations auf den Philippinen

Full-Stack Developers (Data Applications)

Full Stack Developer (Snowflake SQL)