Full-time, Hoofddorp - Amsterdam area (hybrid)
About EverfieldEverfield is a platform with a mission in acquiring, building, and operating vertical market and specialist software companies, focused on European businesses. We invest in and provide support and best practices to software companies in order for them to live up to their full potential by offering a very established approach to promote growth.
Everfield seeks to deliver innovation and growth to its acquired companies by providing best practices and operational support to help identify opportunities and install proven methodologies to accelerate customer and market share. Everfield is located throughout Europe, with offices in the UK, Germany, the Netherlands, France, Poland, Spain, and Latvia.
About the teamAs Financial Data Analyst, you will work closely with Finance teams, Everfield's Business Intelligence team, and regional teams to improve financial reporting and analytics. You will also collaborate with data engineers to create sustainable data pipelines and turn financial data into actionable insights.
In this role, you will become a key member of the Business Intelligence (BI) team. The BI team creates value for various stakeholders (CEO, Finance, COO, Payments, and Everfield's portfolio companies) by creating insights, delivering analysis, automating reporting processes, and improving data quality.
The team builds pipelines with Synapse to ingest data into our data platform, uses Databricks for data transformation, and Power BI for data visualization. For analytics, the team also uses SQL and Python.
The scope of the team is expected to scale with the company's growth and maturity level. Everfield will scale from 40 portfolio companies to approximately 90 companies in the next 4 years.
What you will do- Requirements Gathering
- Align with key stakeholders to understand reporting requirements.
- Create feature development and communication plans.
- Identify new financial data variables to be captured on a portfolio level.
- Data Analysis
- Perform exploratory data analysis to validate feasibility and propose enhancements.
- Suggest alternatives if requirements cannot be met.
- Data Visualization
- Design proof-of-concept solutions for user acceptance testing.
- Maintain and update Power BI reports and dashboards.
- Data Ingestion, Verification, and Validation
- Extract raw financial data from NetSuite and other upstream sources.
- Improve data quality and efficiency.
- Support portfolio companies with quality assurance of their financial data.
- Data Modelling and Transformation
- Build data systems and pipelines based on a medallion architecture.
- Automate workflows using Python (Pandas, PySpark).
- Compliance & Security
- Create and maintain a financial data glossary.
- Self-starter with an entrepreneurial mindset and customer?'centric approach.
- At least 3-5 years of experience in financial data analysis within an international or complex environment.
- Strong experience with NetSuite ERP (data extraction and reporting).
- Hands?'on experience with Python (Pandas, PySpark) and Power BI (DAX, data modelling).
- Knowledge of SQL and data modelling.
- Experience working in a DevOps or Agile environment.
- Fluent in English.
- Above all, a great colleague: enthusiastic, approachable, honest, committed, result?'focused, and a team player.
- Grow your career in a fast?'paced and growing organization.
- Enable exponential growth by designing a world?'class data platform.
- Work with the latest data analytics technologies.
- Long?'term career opportunities.
- Collaborate closely with leadership teams within the headquarters and portfolio companies.
- Flexible work environment with offices around Europe (Netherlands, UK, Spain, France, Poland, Germany).
- Initial call with Talent Acquisition Lead, Maria (0.5h)
- First interview with Hiring Manager, Tom (0.75h)
- Technical assessment, a Case Study (1.0h)
- Final interview, a meeting with the team (0.75h)
We look forward to reviewing your application!
#J-18808-LjbffrSalarisomschrijving€60000.00 - €80000.00 monthly