Senior Data Analyst (m/f/d)

Springtime Technologies is a dynamic and innovative software company specializing in the development and delivery of cutting-edge SaaS solutions using the latest trends in AI for accounts payable automation. More than 200,000 business users in 70 countries use our cloud software already. The company was founded in 2004 by a team of AI experts and has offices in Austria, Germany, and the Philippines.

As a Senior Data Analyst, you’ll design and manage data pipelines, develop insightful data models, and craft clear visualizations and dashboards. You’ll collaborate with stakeholders to grasp data requirements and effectively communicate complex analysis through visual, written, and verbal channels.

According to the collective agreement, a minimum salary of Euro 3,724 gross per month applies to your position. Depending on your experience and qualifications, we offer an overpayment in line with the market.

Your tasks

• Develop and maintain data pipelines (ETL) from source systems to Data Warehouse (DWH).
• Develop and maintain data models.
• Create data dashboards, charts, and visualizations.
• Extract insights from extensive datasets related to accounts payable workflow through analysis and interpretation to derive meaningful insights.
• Monitor and review data quality and the accuracy of dashboards.
• Collaborate with both internal teams and external partners to gain a deep understanding of data requirements and structure.
• Identify opportunities to streamline and automate financial procedures.

Your profile

• Several years of professional experience in the data analytics/engineering field (minimum 5 years).
• Experience in building data pipelines (Apache Airflow, SSIS experience is advantageous).
• Proficient with analytical/reporting tools (Power BI, Tableau, Apache Superset are preferred).
• Skilled in programming for data manipulation (DAX, SQL, and Python are preferred).
• Well-versed in the use of relational database systems, such as MS SQL Server, along with data management techniques.
• Familiarity with constructing and refining data models (SSAS, Clickhouse experience is advantageous).
• A clear understanding of the significance of data governance, coupled with practical experience in managing data governance elements such as data glossaries and data lineage.
• Capability to ensure data integrity through quality checks, validation, and integration.
• Competence in translating complex data sets into comprehensible visual reports and dashboards.
• Knowledge of financial processes and experience with accounts payable processes are advantageous.