Data & Automation Engineer (m/w/d)

reltix GmbH; Düsseldorf; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

reltix GmbH is looking for a Data & Automation Engineer based in Düsseldorf, Germany. In this role, you will own the data and automation backbone, working across finance, sales, and reporting to automate processes and improve data quality.

You will build the automation layer, manage data pipelines, and ensure reporting aligns with operational needs. Ideal candidates have strong skills in data engineering, SQL, and Python, with a clear focus on automation and data quality.

Qualifikationen

• Solid data engineering skills in pipelines, ETL/ELT, and data modelling.
• Hands-on experience with SQL and Python.
• Experience with automation tools like n8n and APIs.

Aufgaben

• Build and run the automation layer for invoice ingestion and classification.
• Own the data pipelines for accounting, CRM, and marketing.
• Develop reporting and analytics for decision-making.

Kenntnisse

Data engineering

SQL

Python

Automation instinct

Data quality focus

Tools

Snowflake

n8n

Metabase

Jobbeschreibung

The German property management industry is one of the oldest and least digitalised service sectors in the country: file folders, fax machines, no transparency for owners, weeks‑long response times, and a chronic shortage of skilled workers. Most players respond in one of two ways: they sell software to incumbents without experiencing the operational reality, or they buy up existing management firms and bolt software onto paper‑based processes. reltix has actively chosen a third path. Inside a single technical infrastructure, we unite operational management and the knowledge that comes from actually offering the service with the digitalisation of data from the properties we manage. That gives us an operating system for property management: the system teams run on, the source of truth for every property, and the platform workflows and partners plug into. The result is an AI‑enabled service business where requests aren’t passed along, they’re answered directly. Whether through the manager’s software interface, the voice agent on the phone, or the owner’s chatbot, because the full context of the property is available everywhere and the system can act on it. Within the wider real estate industry the property manager acts as a platform between the owner and every single service around the property. From banking, electricity, heating, and internet all the way to major renovation projects, this ecosystem spans every adjacent part of the real estate sector. This unique position allows us to not just provide this infrastructure internally but instead to open it up, so reltix becomes the context layer and the operating system of the entire real estate industry. Founded in 2025, we’ve gone from zero to 4,000+ customers and a team of over 30+ people in little more than a year. With funding secured and a third office in Frankfurt planned, we are looking to expand our tech team to help us scale this vision.

reltix is an AI‑native service company: data and automation aren’t a feature, they’re how the business runs. As Data & Automation Engineer, you own the layer that keeps the company running behind the scenes, across finance, sales, marketing, and reporting. You sit at the seam between operations, finance, GTM, and engineering. You work with the people running the business day to day, find where the manual work and friction sit, and ship the data flows and automations that take them away: bank feeds reconciled, invoices ingested and posted, leads routed and enriched, campaigns finally measurable, dashboards the company can actually steer by. Because reltix runs on one backbone, none of this is walled off from the product. The data you structure for the back office is the same context the product, the voice agent, and the owner chatbot draw on, so product and AI work is always within reach when there’s a problem worth solving there. Own the back‑office data and automation backbone end to end. Books that close, leads that get followed up, campaigns that get measured, numbers founders can trust. The work that lives in someone’s inbox, spreadsheet, or PDF folder today should end up inside the system: structured, queryable, automatable. And when you see something broken, slow, or manual anywhere in the company, you fix it rather than file a ticket.

What you’ll do

• Build and run the company’s automation layer in n8n and code: invoice ingestion and classification, bank‑feed reconciliation, posting, lead routing and enrichment, internal tooling.
• Own the back‑office data pipelines in and out of reltix: accounting, invoices, contracts, bank feeds, CRM and sales data, marketing channels, third‑party APIs.
• Own the data infrastructure end to end. Snowflake is yours: warehousing, modelling, transformations, quality, cost.
• Build the reporting and analytics the company steers by, and run the analysis behind real decisions: where revenue comes from, where leads stall, where processes leak time and money.
• Plug AI in where it earns its place: document and invoice parsing, classification, enrichment, anomaly detection, agent workflows that close out tasks autonomously.
• Own customer and portfolio migrations from legacy systems into reltix, cleanly and at scale.

Requirements

• Solid data engineering: pipelines, ETL/ELT, data modelling, warehouses and relational databases.
• Strong with SQL and Python, comfortable in a modern stack, not religious about tools.
• Hands‑on with a stack like ours: Snowflake (or equivalent warehouse), n8n (or equivalent automation tooling), Metabase (or equivalent), and APIs.
• A real automation and AI instinct: you see manual work and immediately see the pipeline, agent, or workflow that replaces it.
• Strong care for data quality, especially where finance and reporting numbers are concerned.
• A pragmatic, shipping mindset and ownership as a default.

Upsides

• A foundational seat in a small team at the centre of how the company runs, on the same backbone the product runs on.
• End‑to‑end ownership of the stack, with the mandate to choose and evolve the tools.
• A direct line to the founders, the operations team, and real customers. No bureaucracy between you and the problem.
• A category that’s wide open: the data and automation infrastructure for an industry that has never had one.