Founded in 2010, our client is a financial technology company from Latvia, specializing in loans, leasing, and other financial services for both individuals and businesses. With over a decade of experience, they serve more than 260,000 clients and have issued loans exceeding 145 million euros. Their mission is to provide fast, simple, and reliable financial solutions tailored to their clients' needs.
They are looking to recruit 1 mid-level or senior-level Data Analyst. Their Data Analytics team of 4 experienced professionals primarily takes care of the analysis of client applications throughout the acceptance process. The team is also involved in marketing data analytics using data from Google Analytics, Facebook ads, affiliate marketing etc.
Their Offer to You:
- Stability and work environment that prioritizes and promotes work-life balance;
- Access to paid training opportunities, company events, engaging speakers, and other inspiring initiatives;
- Salary for this role is from 2800 - 4000 EUR gross or more depending on your experience. If you have higher expectations, please let us know;
- Hybrid working model. The data team usually is working 4 days a week from their modern A-class business center Jupiter Tower in Riga (free parking);
- Paid lunches at the office every day;
- Health insurance.
Minimal Requirements to Apply:
- You have at least around 2 years of experience with data analysis;
- Strong analytical skills and ability to design visually appealing dashboards and reports;
- Experience with Power BI, demonstrating understanding of data modeling, visualization and analysis;
- Strong proficiency in SQL, ensuring the ability to retrieve, manipulate, and analyze data from databases;
- You can effectively collaborate with stakeholders, grasp their requirements, and present insights and recommendations;
- You can communicate in Latvian and English, both spoken and written.
Considered as Plus if you have any of the following:
- Expertise in DAX language;
- Familiarity with Microsoft Fabric cloud platform and its underlying solutions;
- Experience with data analytics, integration, cleansing, and transformation tools. For example, Python and REST APIs.
Key Responsibilities:
Data Analysis
- Utilize data from internal and external sources to tackle intricate business challenges, offering actionable insights for daily operations and decision-making;
- Conduct ad hoc analysis aligned with business needs to uncover trends, patterns and actionable insights for business improvement;
- Develop presentations summarizing analysis/report findings along with recommendations, effectively communicating results to leadership and key stakeholder.
Reporting and Data Quality
- Participate in the development and maintenance of operational reporting portfolio to enhance business operations management and decision-making;
- Generate business requirement documentation for any reporting or integration initiatives;
- Uphold data governance standards, drive enhancements to existing data products, and stay informed on industry trends.
Data Integration
- Collaborate closely with data engineers to enhance and broaden existing datasets.
