Software Engineer, Data Platform

Loop3; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

100% Remote

Salary in USD

Technical Leadership

Learning Budget

14 Days PTO

Flexible Schedule

High Autonomy

Job summary

Winclap is seeking a Data Platform Engineer to build the data backbone for AI-powered decision tools. You will design scalable pipelines, reliable infrastructure, and developer tooling to transform raw financial data into fast, investable insights.

You will own pipelines, APIs, orchestration, and platform observability, collaborating with product and leadership. The role emphasizes strong system design, Python fluency, and hands-on data-system expertise.

Qualifications

• 4-6+ years of backend or data engineering experience building production-grade systems.
• Strong system design chops — you've designed and shipped data platforms or infrastructure that people actually depended on.
• Python proficiency — your primary tool for pipelines, transformations, and automation.
• Data systems fundamentals — you understand databases (relational and otherwise), concurrency, event-driven architectures, and why consistency is hard.
• Performance debugging — you've diagnosed slow queries, bottlenecked pipelines, and overcomplicated schemas, and you know how to fix them.
• Generalist at heart — you can model complex data, build backend APIs, and wire up orchestration without needing a specialist for every layer.
• Executive communication in Spanish and English — you explain data architecture decisions clearly to both engineers and non-technical stakeholders.
• Ownership mindset — you take features from design through deployment and don't drop the ball in between.

Responsibilities

• Data ingestion pipelines that reliably pull from multiple sources.
• Transformation & enrichment layers turning multi-source data into clean, investable data.
• Backend services and APIs that serve real-time signals to AI agents and product surfaces.
• Developer tooling and abstractions to boost team productivity.
• Platform observability — monitoring, alerting, and data quality frameworks.
• Orchestration systems coordinating multi-step data workflows across the stack.

Skills

Backend engineering

Python

Data pipelines

System design

Databases

Distributed systems

Performance tuning

Bilingual (Spanish/English)

Tools

Snowflake

AWS

GCP

Azure

Kafka

Job description

Software Engineer - Data Platform - Powering the people who bet on the future

What We're Actually Building

We're engineering decision-making infrastructure for some of the world's top 50 VC firms. When elite investors evaluate whether that AI biotech startup is the next $10B company or just impressive slide decks, our systems provide the signal that matters.

The data underneath that intelligence is our competitive moat — and that's where you come in.

This isn't a data analyst role. This is backend engineering applied to data infrastructure at scale.

The reality: We build AI-powered dealmaking intelligence for private capital. As a Data Platform Engineer, you'll architect the data backbone that makes it possible — scalable pipelines, reliable infrastructure, and the developer tooling that lets our team build data products at speed. You'll design systems that ingest market signals from dozens of sources, transform raw financial data into investable insight, and make it all queryable in milliseconds.

What you'll own: The data platform that powers everything else. Pipelines, APIs, orchestration, and the infrastructure that keeps it running — reliably, at scale.

Why Loop3

Impact That Compounds: The systems you build directly shape how capital flows to breakthrough companies. Bad data means bad decisions. Your pipelines are the foundation every investment recommendation stands on.

Real Data Engineering Depth: Work at the intersection of distributed systems, event-driven architectures, and financial data at scale. Multi-source ingestion, complex transformation pipelines, Snowflake optimization, streaming architectures — this is the kind of data complexity most people only read about on Hacker News.

Pure Meritocracy: Can you design reliable data systems and ship them with minimal oversight? That's what counts. No politics, no credential theater — just engineering excellence and measurable business impact.

High Agency Paradise: You’ll make architectural decisions and choose your tools. This isn't following someone else's roadmap — you're building it alongside product and business leaders. We trust you to know what's right.

What You'll Architect

• Data ingestion pipelines that reliably pull from Pitchbook, financial APIs, proprietary data sources, and anything else that moves markets
• Transformation & enrichment layers that turn messy, multi-source financial datasets into clean, queryable, investment-grade data
• Backend services and APIs that serve real-time signals to our AI agents and product surfaces
• Developer tooling and abstractions that make the rest of the team dramatically more productive when building data products
• Platform observability — monitoring, alerting, and data quality frameworks that catch problems before they reach investors
• Orchestration systems that coordinate complex, multi-step data workflows across our entire stack

Our stack: Python, Node.js/TypeScript, Snowflake, Azure/GCP/AWS (Lambda, S3, SQS, EventBridge, RDS, AppRunner), SST/Terraform, SQL/NoSQL, Kafka-style event streaming.

But really — if you can design data systems that scale and make sound architectural trade-offs, the specific tools are implementation details you'll master.

What We're Looking For

Non-Negotiables

• 4-6+ years of backend or data engineering experience building production-grade systems
• Strong system design chops — you've designed and shipped data platforms or infrastructure that people actually depended on
• Python proficiency — your primary tool for pipelines, transformations, and automation
• Data systems fundamentals — you understand databases (relational and otherwise), concurrency, event-driven architectures, and why consistency is hard
• Performance debugging — you've diagnosed slow queries, bottlenecked pipelines, and overcomplicated schemas, and you know how to fix them
• Generalist at heart — you can model complex data, build backend APIs, and wire up orchestration without needing a specialist for every layer
• Insatiable learning drive — always exploring new approaches; you actually read engineering blogs and experiment with new tools
• Executive communication in Spanish and English — you explain data architecture decisions clearly to both engineers and non-technical stakeholders
• Ownership mindset — you take features from design through deployment and don't drop the ball in between.

What Excellence Looks Like

• You've designed data pipelines in production that handled real volume and real messiness (and have the war stories to prove it)
• You understand data consistency, idempotency, and late-arriving data — not just theoretically, but from having been burned by them
• You can translate ambiguous business data requirements into architecture that actually scales
• You know when to reach for Snowflake and when a well-placed Postgres index is all you need (and can defend both)
• You build with downstream developers in mind — your APIs and abstractions make your teammates faster

Nice to Have

• Experience with event streaming systems (Kafka, Kinesis, Flink, or similar)
• Exposure to cloud-native data services on AWS or GCP (especially Redshift, BigQuery, Dataflow)
• Familiarity with Data Mesh principles, data catalogs, or data lake architectures
• Experience building internal developer platforms or tooling for data teams
• Comfort with containerization (Docker) and Kubernetes for data workloads
• Understanding of Snowflake optimization — clustering, materialized views, cost control

Our Values in Action

Loop as a Way of Working: We build, ship, learn, iterate. Every loop makes us better. Perfection isn't a final state — it's a process.

Curiosity as Fuel: We stay hungry. Exploration keeps us sharp and ahead of the curve. Curiosity makes us more human.

Ownership & Making Things Happen: We kick down doors. You'll think like a founder — anticipate, initiate, deliver. We don't wait for permission.

Technology with Purpose: We build systems that amplify people and level the playing field. Our tech enables people to focus on what makes them human: judgment, creativity, and real connections.

What We Offer

• 100% Remote — Build from wherever you're most effective
• Salary in USD
• Technical Leadership — Shape data architecture and drive platform vision
• Tech Budget — Hardware, software, tools you need to do your best work (Cursor Pro, Claude Pro, and more)
• 14 Days PTO plus holidays
• Learning Budget — Conferences, courses, cutting-edge tech exploration
• Flexible Schedule — Real adaptability, objective-based
• High-Autonomy Culture — Complete creative freedom in exchange for exceptional results