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Senior Analytics Engineer

Scalable Capital GmbH · Berlin | Deutschland · Hybrid, Onsite

Gehalt auf Anfrage

Gefunden am 02.06.2026

Match

84%

Fit in Skills, Kultur und Entwicklungspfad.

Beschreibung

Job Zusammenfassung In dieser Position entwickelst du datengetriebene Lösungen, baust robuste Pipelines auf und erstellst präzise Datenmodelle, die internen Teams zur Entscheidungsfindung und Analyse dienen. Job Zusammenfassung In dieser Position entwickelst du datengetriebene Lösungen, baust robuste Pipelines auf und erstellst präzise Datenmodelle, die internen Teams zur Entscheidungsfindung und Analyse dienen. Deine Rolle im Team As an analytics engineer in the regulatory reporting and data platform teams of our data engineering tribe, you play a crucial role in owning our data stack and delivering effective data models. You will be instrumental in building and maintaining robust data pipelines, making critical and reliable data available to various stakeholders throughout the company, and contributing to our data-driven culture. Shape the data coming from a mixture of internal services into consistent, conformed models, and then further transform this data to serve specific teams and use cases. Prepare and clean structured and unstructured data and develop high-quality data models for reporting purposes. Extend our AWS-based lakehouse by integrating data and building regulatory use cases to empower various teams in decision-making, drive innovation, optimise performance and ensure compliance. Design and implement data testing and monitoring to ensure the accuracy, reliability, and performance of data pipelines. Collaborate closely with highly ambitious and skilled people in our growing data teams, as well as product & engineering colleagues to release smart features for our products. Maintain trustworthy documentation and data catalogues to ensure clarity, accessibility and correct governance of the data on our platform. Assist colleagues with understanding the data landscape, resolving problems and accessing data as needed. Stay up to date with the latest industry developments in data modelling and share your expertise best practices within the company. Unsere Erwartungen an dich Ausbildung University degree in computer science, mathematics, natural sciences, or a similar field. Qualifikationen Specific understanding of AWS and Athena is a plus. Excellent SQL skills, including advanced concepts such as window functions and an ability to optimise for performance while building queries. Ability to work with Python (particularly data handling packages) is desirable. Ability to work with version control and CI/CD as part of a robust and controlled development lifecycle. Understanding of the needs of working in a tightly-governed and regulated environment. Strong problem-solving and organizational skills. Fluent English communication and presentation skills. Erfahrung Significant knowledge and experience in designing and building data models for business analysis and regulatory purposes. Experience of working with cloud-based data lake services and an understanding of data lake concepts. Experience with dbt or similar frameworks is essential. Interest in financial services and markets, ideally with previous working experience in this domain and an understanding of how to model business concepts in financial services in data. Benefits Essen & Trinken ☕️ Kaffee, Tee o. Ä Work-Life-Integration 🕺 No Dresscode 🚌 Gute Anbindung 🏝 Extra Urlaubstage 🏠 Home Office 🅿️ Mitarbeiterparkplatz ⏰ Flexible Arbeitszeiten Gesundheit, Fitness & Fun 🎳 Team Events Mehr Netto 💻 Notebook zur Privatnutzung Themen mit denen du dich im Job beschäftigst FinTech Big Data Metadaten Level: Senior Job Feld: BI, Data Anstellung: Vollzeit Vertragsart: Unbefristetes Dienstverhältnis Arbeitsmodell: Hybrid, Onsite Unternehmenstyp: Etablierte Firma Branche: Banken, Finanz, Versicherung Ort: Berlin | Deutschland

Tech Stack

AWSPythonSQL

Warum passt du zu dieser Stelle?

Fit technisch: Stark auf Backend und API-Architektur.

Gaps: Fehlende Tool-Erfahrung in 1-2 Schlüsselbereichen.

Success-Wahrscheinlichkeit: Hoch bei schneller Einarbeitung.