Lead Data Engineer

Why this role

ZYNE is an independent scale-up backed by VERBUND, Austria's leading electricity provider, and TTTech. We build the energy management platform that connects and controls distributed energy assets, PV, industrial batteries, EV charging, across customer sites in Austria and Germany, from edge devices on the factory floor to the cloud. Our largest engineering hub is in Novi Sad, and every measurement, forecast, and control decision runs through the data architecture you will own.

You will lead the Data Platform team and make the foundational calls that shape the platform for years: separating streaming and analytical paths, designing a low-latency serving layer, building auditable decision logs for provable energy optimization, and deciding what runs in the cloud versus on the edge. This is design work, not legacy maintenance, and the architecture decisions are yours to make and defend.

You join a small, focused team across Novi Sad, Vienna and Munich, reporting to the Director of Product Development & Operations.

What you'll own

• Architecture: end-to-end data platform design, from MQTT/event ingestion through lakehouse storage to the APIs consuming teams build on
• Foundational decisions: streaming vs. batch separation, hot serving path, auditable event and decision logging, cost-driven re-platforming of core workloads
• Data contracts and governance: versioned schemas that let producing and consuming teams work independently
• The team: a small, focused team backed by a principal-level data consultant, with headcount growing alongside the roadmap; you run the team's planning and coaching your way
• Hands-on work: this is a builder-lead role; you design, review, and ship alongside the team

What you bring

• You have designed and operated production data platforms on a modern lakehouse or warehouse stack (Databricks, Snowflake, BigQuery, or open-source equivalents); we hire for the concepts, not the vendor badge
• Expert SQL and strong Python; you can still out-review your team on a Spark job
• You have made the streaming-vs-batch call in production and can argue it in both directions
• You design for resilience and auditability: failure isolation, quality gates, immutable logs
• You have grown engineers and set direction without micromanaging
• Fluent English (working language across all locations)

Nice to have: Azure data stack, time-series workloads, IoT or energy domain, data contract tooling, applied ML exposure, experience working with AI coding agents.

Our stack today

Azure, Spark-based lakehouse with medallion architecture, Event Hub, MQTT-connected industrial edge devices. Nothing is sacred: decisions are documented as ADRs, and you will write the next ones.

How we work

You'd join the team that owns the product end to end, from edge devices to the data products customers rely on. Our Novi Sad office is the largest engineering hub, with occasional travel to Vienna or Munich for team workshops, roughly quarterly. Small, focused teams of 4–5 that leads run independetly; your contributions are visible immediately. AI-augmented engineering is the default, with dedicated enablement.

High ownership: given a problem, you drive it to completion without constant guidance. Your work directly determines the performance of real energy assets.

Hiring process

No take-home assignments, no algorithm puzzles. Intro chat → one or two technical conversation(s) → offer. Process to be completed within a week or two after we make the first contact.