[Hiring] Data Engineer @AgentixLake GmbH

Role Description

Own the data foundations that analytics and AI depend on. You will lead the engineering of cloud data platforms and lakehouse solutions, from source integration and modelling through deployment, performance tuning and reliable operation.

Our data engineering services cover platform modernisation, analytics engineering and DataOps. We work with AWS, Snowflake, Databricks, Google Cloud and on-premises technologies, selecting the stack that fits the customer’s requirements.

What you will do

• Design and deliver batch or streaming pipelines that integrate operational databases, APIs, files and event sources.
• Build maintainable data models and transformations for analytics, governed metrics and AI applications.
• Implement lakehouse or warehouse architectures, choosing appropriate storage formats, partitioning and processing strategies.
• Establish data quality tests, orchestration, lineage, monitoring and recovery procedures; investigate incidents and remove recurring causes.
• Manage infrastructure and deployments through version control, infrastructure as code and CI/CD, with appropriate access controls.
• Lead technical delivery with customers and colleagues, review code and document the decisions needed to operate and extend the platform.

Qualifications

• Substantial experience delivering and operating production data platforms, including responsibility for technical decisions and service reliability.
• Strong Python and SQL, sound data modelling and a practical understanding of distributed processing and orchestration.
• Depth in at least one major environment such as AWS, Snowflake, Databricks or Google Cloud, with the ability to assess alternatives.
• Experience with tools such as dbt, Airflow or Dagster, and with testing, Git, CI/CD and infrastructure automation.
• The ability to explain performance and cost trade-offs, scope a deliverable and communicate clearly with technical and business stakeholders in English.
• Experience with Apache Iceberg, Spark, Kafka, Terraform or data foundations for RAG and AI agents is valuable.
• AWS or other relevant certifications support your application; delivery evidence matters most.

What you can expect

You will take responsibility for substantial engineering work, collaborate directly with the founders and influence our reusable delivery patterns. The role combines implementation with platform architecture and practical technical consulting.

How to apply

Use the Apply button on this page to submit your CV, location and availability. Describe one production platform you owned, your individual contribution and a measurable improvement or operational problem you resolved. An anonymised case summary is sufficient; please do not share confidential client material.

We welcome applicants of all backgrounds. If the core responsibilities match your experience, we would like to hear from you.

Company Description

AgentixLake GmbH is a data engineering and AI engineering consultancy based in Hamburg, Germany. We help businesses design, build and operate production-grade data platforms and AI systems on infrastructure they control, including their own cloud accounts and on-premises environments.

• Our services connect data and AI platform architecture with hands-on delivery: cloud data platform engineering, lakehouse modernisation, analytics engineering, AI-native applications and agentic systems.
• We also build document intelligence workflows, enterprise retrieval-augmented generation and private AI deployments, with data quality, access controls, evaluation and observability considered throughout delivery.
• We work with AWS, Snowflake, Databricks, Google Cloud and on-premises technologies according to the customer’s requirements.
• AgentixLake is an AWS Select Tier Services Partner and a Certified Services Partner in Anthropic’s Claude Partner Network.
• Our commercial focus is the DACH market—Germany, Austria and Switzerland—and the Gulf region, while we remain open to selected international opportunities.
• Engagements bring architecture and technical advisory together with implementation and operational ownership.
• Our engineers work on practical problems: trustworthy data pipelines, AI assistants connected to governed information, document extraction for downstream systems and agents with clear permissions and human review.
• We value delivery experience, clear technical judgement and maintainable software.