Data Engineer

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Infinity Constellation

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2023

💼 Consulting

🏭 Manufacturing

📦 Logistics

Consulting • Manufacturing • Logistics

Infinity Constellation is the first AI Holding Company dedicated to helping elite founders build AI companies that can operate at unprecedented speeds. By leveraging advanced AI platforms, Infinity Constellation aims to reinvent traditional venture models, focusing on efficient structures that allow businesses to generate profits rapidly with minimal resources. The company supports its portfolio through various operational services, enabling founders to scale and thrive in the rapidly evolving AI landscape.

📋 Description

• Ship scrapers and ingestion flows against messy, sometimes adversarial sources, using HTTP/2 clients, TLS-fingerprint evasion, and browser automation fallbacks, and keep them resilient as sources change • Own Postgres schema design and migrations end to end across per-country and per-domain schemas • Build and maintain medallion (bronze → silver → gold) transforms that are idempotent, content-hashed, and lineage-tracked • Implement and defend index methodology: normalization, weighting, and composite construction where the math verifiably says what it claims (our scoring core is held to 100% test coverage) • Assess data feasibility early, clarify requirements with partners, and convert ambiguous index ideas into executable plans • Take an index end to end: sourcing, validation, methodology, publication, and refresh planning • Operate pipelines on our orchestration stack (Prefect dispatching per-flow ECS Fargate tasks) with observability everywhere

🎯 Requirements

• Strong Python and SQL; you have designed Postgres schemas and owned migrations (SQLAlchemy and Alembic, or equivalents) in production • Data pipeline experience with a lakehouse/medallion mindset: idempotent ingestion, content hashing, and lineage are habits, not aspirations • Web scraping beyond requests: anti-bot evasion, browser automation, and resilience against messy or hostile sources • Statistics literacy for index methodology: winsorization, normalization, weighting, and sensitivity testing, and you can reason about whether an index's math supports its claims • Comfort with modern Python tooling and CI discipline: typing, linting, coverage gates, and conventional commits • Product discovery instincts: you talk with partners in plain language, assess data feasibility before committing, and flag what is proven versus assumed • End-to-end ownership: you are a pragmatic generalist who moves across data, backend, infrastructure, and basic product decisions in an uncertain environment

🏖️ Benefits

• High-impact work at the intersection of AI and critical infrastructure regulation • End-to-end ownership of indices, from raw source to published methodology • Small team with outsized influence; your feasibility calls shape what we build • Modern AI-native development environment (Claude Code, Cursor, multi-model orchestration) • Remote-first • Competitive compensation