Data Engineer (Business Financing sphere)

coherentsolutions; Deutschland; Hybrid; EUR 65.000 - 90.000; Vollzeit

Benefits dieser Stelle

Health insurance

Sports and wellness activities

Referral program

Work‑anniversary recognition

Additional vacation days

Zusammenfassung

coherentsolutions is seeking a hands-on Data Engineer to build and scale a Snowflake-centered data platform supporting Treasury, Finance, and expanding domains. You will own production pipelines, data models, and workflow migrations, delivering reliable data products with strong quality controls.

The role requires 4+ years in data engineering, production dbt work, and proficiency in SQL. Candidates should be comfortable with US Central Time collaboration and using AI-assisted tools.

Qualifikationen

• Four+ years of data engineering experience, with hands-on Snowflake work.
• Practical dbt experience and production data transformations.
• Experience with Dagster, Airflow, or similar workflow tools.
• Strong SQL and analytical data-modeling skills.
• Experience in data quality checks and monitoring practices.
• English proficiency at B2 level or higher, with familiarity with AI-assisted development tools.

Aufgaben

• Build and maintain production data pipelines and reusable data products in Snowflake.
• Develop transformation logic and data models with dbt for governed engineering.
• Migrate Alteryx workflows to production-ready platform components.
• Create and maintain orchestration workflows using Dagster, Airflow, or similar tools.
• Validate outputs, investigate discrepancies, and resolve transformation defects.
• Implement data-quality checks and monitoring in collaboration with analytics, BI and governance peers.

Kenntnisse

SQL

Data modeling

Analysis

English (B2)

Tools

Snowflake

dbt

Dagster

Airflow

Fivetran

MetricFlow

Cursor

Jobbeschreibung

**Role overview**

Build and scale a Snowflake-centered data platform supporting business-financing operations. The initial delivery area is Treasury and Finance, with the platform expected to expand into additional domains over time. This is a hands‑on production data engineering role involving pipeline development, workflow migration, data modeling, and quality controls.

**Responsibilities**

• Build and maintain production data pipelines and reusable data products in Snowflake.
• Develop transformation logic and data models with dbt, following governed engineering practices.
• Convert existing Alteryx workflows into managed, production‑ready platform components.
• Create and maintain orchestration workflows using Dagster, Airflow, or a comparable tool.
• Validate outputs, investigate data or business‑logic discrepancies, and resolve transformation defects.
• Implement data‑quality checks and monitoring while collaborating with analytics engineering, BI, and data governance peers.

**Requirements**

• At least four years of data engineering experience, including substantial hands‑on work with Snowflake.
• Practical experience building with dbt and transforming modeled data in a production environment.
• Experience with Dagster, Airflow, or another workflow orchestration platform.
• Strong SQL and analytical data‑modeling skills.
• Demonstrated ability to maintain reliable data pipelines and apply data‑quality or monitoring practices.
• English proficiency at B2 level or higher, plus comfort using AI‑assisted development tools such as Cursor or similar software.

**Nice to have**

• Snowflake certification.
• Substantial availability for collaboration during US Central Time hours, particularly from 2:00 PM Central Time onward.
• Experience with Fivetran, MetricFlow, or LLM‑assisted engineering workflows.

**Benefits and work setup**

• Remote and hybrid work options are available.
• Technical and non‑technical training, internal conferences, and expert‑led learning events.
• Mentorship and support from an experienced colleague.
• Health insurance, sports and wellness activities, and a referral program.
• Work‑anniversary recognition and additional vacation days as employment tenure increases.