Data Operations Analyst

Nilus

Nilus

IT, Operations
Tel Aviv District, Israel
Posted on Tuesday, July 2, 2024

About Nilus

All companies need to have a clear understanding of their financials to improve their cash performance. Yet, finance teams still rely on Excel to gather data from multiple bank accounts, making it difficult to see their cash positions, identify cash flow trends, and generate insights to help the business grow.

That's where Nilus comes in.

At Nilus, we're building a strategic cash management platform for modern finance teams that provides real-time cash visibility, forecasting, and reconciliation - all powered by AI. Nilus is a fast-growing fintech startup backed by top VCs like Bessemer Venture Partners, Felicis Ventures, Better Tomorrow Ventures, and Symbol. We're all passionate about revolutionizing the role of finance teams today, and most of us - across engineering, sales, marketing, and product - come from previous roles at fintechs.

What are we looking for?

We are looking for a Data Operations Analyst to join our Operations team. You will be primarily responsible for data validation, monitoring, and ensuring the accuracy, integrity, and reliability of our data systems.

What you will be doing

  • Monitor data quality and integrity across various operational systems and databases.
  • Perform data cleansing, validation, and transformation tasks to ensure accuracy and consistency
  • Develop, optimize, and maintain complex SQL queries for data analysis and reporting purposes.
  • Perform data cleansing, validation, and transformation tasks to ensure accuracy and consistency
  • Provide insights and recommendations based on data analysis to optimize operational workflows

Qualifications

  • Education : Bachelors degree in Industrial management, data science, economics, accounting or equivalent.
  • Proven experience in data operations, data validation and data integrity.
  • Experience with SQL, Excel, and data visualization tools.
  • Experience with Phyton - must
  • Detail-oriented with a strong commitment to data accuracy and quality.
  • Strong ‘can-do’ approach
  • Excellent teamwork skills