Senior Data Analyst with Tableau

We are looking for a Senior Data Engineer. You will be the backbone of our data platform — designing, building, and maintaining the pipelines, transformations, and APIs that power Finance reporting, analytics, and operational tooling across the organization.

You will work in a modern cloud-first stack centered around Snowflake, collaborating with data analysts, UX designers, and software engineers to deliver reliable, scalable, and well-governed data solutions. This role requires both deep technical expertise and the ability to translate complex Finance data requirements into clean, production-grade engineering.

Your responsibilities:

Data Engineering & Architecture

• Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver Finance data from multiple source systems into Snowflake
• Implement data blending strategies to consolidate data across heterogeneous sources (ERP systems, flat files, APIs, databases) into unified, trusted datasets
• Apply Snowflake-native capabilities: dynamic tables, streams, tasks, materialized views, data sharing, and time travel
• Model data using dimensional and modern approaches (e.g. Data Vault, medallion architecture) appropriate to Finance use cases
• Ensure data quality, consistency, and lineage through robust testing and monitoring practices
• Optimize query performance and cost efficiency within Snowflake
• Pipelines & Orchestration
• Build and maintain data pipelines using orchestration tools such as Apache Airflow, dbt, or equivalent
• Implement CI/CD practices for data pipelines using GitHub Actions or similar, ensuring version-controlled, reviewable, and deployable data code
• Monitor pipeline health, set up alerting, and own incident resolution for data failures
• Backend & API Development
• Design and develop RES
• Tful APIs to expose Finance data to internal web applications and downstream consumers
• Collaborate with frontend and full-stack developers to define data contracts and ensure reliable, performant backend integration
• Implement authentication, authorization, and data access governance appropriate for sensitive Finance data
• Cloud & Infrastructure
• Work within cloud environments (AWS) and apply cloud data warehouse best practices around security, scalability, and cost management
• Contribute to infrastructure-as-code practices where relevant (Terraform or equivalent)

Champion data security and compliance standards, particularly around financial data sensitivity and regulatory requirements

• Collaboration & Standards
• Partner with Finance domain experts and analysts to understand data needs and translate them into technical solutions
• Contribute to and enforce data engineering standards, documentation, and best practices across the teamMentor junior engineers and act as a technical reference point within the domainWe are looking for you, if you have:5+ years of experience in data engineering, with at least 2 years working extensively with Snowflake in a production environment
• Strong hands-on experience with ETL design, data blending, and complex data transformation logic
• Proficiency in SQL (advanced level) and Python for data engineering tasks
• Experience building and maintaining data pipelines with orchestration tools (Airflow, dbt, Prefect, or similar)

Solid understanding of cloud data warehouse concepts: partitioning, clustering, materialized views, query optimization, and cost governance

• Experience working with Finance data (general ledger, cost center structures, P& L, FP& A, or similar domains) is a strong advantage
• Proficiency with GitHub for version control, branching strategies, and collaborative code review
• Experience developing and documenting backend REST AP
• IsFamiliarity with CI/CD pipelines for data workloads
• Nice to Have
• Experience with SAP (S/4HANA, BW4) or other ERP source systems as data origins
• Knowledge of data governance frameworks and metadata management tools (e.g. Collibra, DataHub)

Exposure to Snowflake's data sharing and Marketplace capabilities

• Familiarity with dbt (data build tool) for transformation and testing
• Understanding of dimensional modeling
• Experience in regulated industries (pharma, finance, life sciences)

Tech Stack

• Data Platform: Snowflake
• Orchestration: Apache Airflow / dbtLanguages: Python, SQL
• Version Control & CI/CD: GitHub, GitHub Actions
• Cloud: Azure / AWSAPI: REST, FastAPI or equivalentBI & Consumption Layer: Tableau or equivalentWe offer:

Participation in interesting and demanding projects.

Flexible working hours.

A great, non-corporate atmosphere.

Possibility to work remote or hybrid (2 days per week from the office).

Opportunities for development and promotion.

Attractive package of benefits.

We reserve the right to contact the selected candidates.