Forward Deployed Engineer - Integrations & Customer Success (f/m/d)

United States Digital Space LLC; Hamburg; Vor Ort; EUR 90.000 - 110.000; Vollzeit

Benefits dieser Stelle

Hybrid work model with Hamburg office

Salary + equity

Vacation 30 days

Zusammenfassung

United States Digital Space LLC in Hamburg is seeking an experienced Data Engineer to own the reliability and growth of our data infrastructure end‑to‑end and to drive data pipelines for our AI models.

You will expand connectors beyond Shopify and Amazon, work with customers to understand data sources, and scale pipelines while reducing cost.

This role requires fluent German and English, 3+ years in data engineering, and a hands‑on approach to DataOps/MLOps in a cloud environment.

Qualifikationen

• Fluent German and English, both written and spoken.
• 3+ years experience in data engineering.
• 3+ years Python for data manipulation (Pandas, Polars).
• Deep proficiency in SQL and PostgreSQL.
• Experience building scalable streaming, event‑driven, and batch data pipelines for web applications and AI models.
• Proven ability to set up and maintain robust testing environments and DataOps/MLOps workflows.
• Familiarity with infrastructure and containerization frameworks such as Kubernetes, Docker, Terraform.
• End‑to‑end expertise in designing scalable data platforms, including storage (S3/Parquet), pipelines, APIs, and connectors with layered architecture.
• Strong product intuition, proactive ownership mindset, and comfort with ambiguity.
• Daily use of AI tools for workflow automation (testing, development, staging, production).

Aufgaben

• Expand the data connector ecosystem beyond Shopify and Amazon and maintain new data sources with stability and customization.
• Work closely with customers to understand their data sources, requirements, and edge cases.
• Take ownership of the Bronze → Silver → Gold medallion architecture, ensuring logical consistency and documentation.
• Scale pipelines for more data, faster processing, and lower cost, while abstracting across customers with unique requirements.
• Improve developer experience with fast iteration cycles and smooth tooling.
• Fully embrace AI tools as core of the workflow, delegating end‑to‑end tasks and building AI‑driven pipelines that remain robust.
• Own the full development lifecycle with automated checks, robust testing environments, and proactive resolution of bottlenecks, inconsistencies, and schema drift.

Kenntnisse

Fluent German

Fluent English

3+ years data engineering

Python (Pandas/Polars)

SQL & PostgreSQL

Data pipelines

DataOps/MLOps workflows

Kubernetes

Docker

Terraform

Airflow

Airbyte

SageMaker

AWS

Tools

Kubernetes

Docker

Terraform

Airflow

Airbyte

SageMaker

Lambda

Databricks

dbt

Apache Spark

EMR

Jobbeschreibung

Overview

We are a fast‑growing AI startup focused on inventory forecasting for e‑commerce brands. You will own the reliability and growth of our data infrastructure end‑to‑end and drive the engineering of data pipelines that power our AI models.

Responsibilities

• Expand the data connector ecosystem beyond Shopify and Amazon and maintain new data sources with stability and customization.
• Work closely with customers to understand their data sources, requirements, and edge cases.
• Take ownership of the Bronze → Silver → Gold medallion architecture, ensuring logical consistency and documentation.
• Scale pipelines for more data, faster processing, and lower cost, while abstracting across customers with unique requirements.
• Improve developer experience with fast iteration cycles and smooth tooling.
• Fully embrace AI tools as core of the workflow, delegating end‑to‑end tasks and building AI‑driven pipelines that remain robust.
• Own the full development lifecycle with automated checks, robust testing environments, and proactive resolution of bottlenecks, inconsistencies, and schema drift.

Qualifications

Must‑have skills

• Fluent German and English, both written and spoken.
• 3+ years of experience in data engineering or closely related roles.
• 3+ years of experience in Python for data manipulation (Pandas, Polars).
• Deep proficiency in SQL and PostgreSQL.
• Experience building scalable streaming, event‑driven, and batch data pipelines for web applications and AI models.
• Proven ability to set up and maintain robust testing environments and DataOps/MLOps workflows.
• Familiarity with infrastructure and containerization frameworks such as Kubernetes, Docker, Terraform.
• End‑to‑end expertise in designing scalable data platforms, including storage (S3/Parquet), pipelines, APIs, and connectors with layered architecture.
• Strong product intuition, proactive ownership mindset, and comfort with ambiguity.
• Daily use of AI tools for workflow automation (testing, development, staging, production).

Bonus / Nice‑to‑have

• Experience in B2B AI startups or scale‑ups.
• Experience with e‑commerce data sets and solutions (Shopify, Amazon Seller Central, Google Ads, Meta Ads, Klaviyo, Channable, etc.).
• Familiarity with big data tools (dbt, dask, Apache Spark, EMR, Databricks, AWS Glue).
• Interest in data science workflows, especially time‑series forecasting (Nixtla, Darts, statsmodels, sktime).
• Contributions to developer experience, data observability, or internal tooling improvements.

Tech Stack

• Programming: Python (Pandas, Polars), SQL.
• Data Storage & Management: PostgreSQL, AWS S3 (Parquet), BigQuery.
• Orchestration: Airflow, EventBridge, Crons.
• AI Tools: Claude Code, CursorAI Agents.
• Containerization: Docker, Kubernetes, Terraform.
• Data Integration: Airbyte (self‑hosted on Kubernetes).
• Processing & ML: AWS SageMaker, AWS Lambda, MLflow.

Benefits

• AI‑first engineering philosophy with full workflow automation.
• Fast‑paced environment with short daily stand‑ups, efficient weekly planning, and autonomous decision making.
• Customer proximity: direct contact with customers during pilot projects.
• Hybrid work model: 50/50 remote with office in Hamburg city centre.
• Permanent full‑time contract with competitive salary (€90,000–€110,000) and equity for senior hires.
• 30 days paid vacation and unlimited paid time off.
• All AI subscriptions, new MacBook Pro and dual monitors, regular team events, quarterly off‑sites, and Wellpass membership for fitness and wellness.

Hiring Process

• Initial screening (30 min).
• Technical interview with CTO (30 min).
• Live coding challenge (90 min).
• Meet the team in Hamburg.
• Offer within two weeks.