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Senior Data Analyst - Financial Services

Yassir

worldwide / Cairo, Egypt / Alexandria, Egypt / Barcelona, Spain / Belgrade / Bucharest / Cape Town, South Africa / Lagos, Nigeria / Nairobi, Kenya / Remote / Sofia / Warsaw / Kyiv

Hybrid

Full-time

Moderate

Summary

Responsibilities

Create conceptual, logical, and physical data models to meet the needs of various business processes.
Optimize data model performance by analyzing and refining database designs and queries.
Collaborate with data architects, data engineers, and business analysts to integrate data across different sources.
Maintain data documentation and ensure clear communication among stakeholders.
Develop, implement, and maintain business intelligence solutions to support decision-making.
Work closely with business stakeholders to understand their data needs and translate them into technical requirements.
Provide support and guidance to data analysts and team members on data-related issues.
Utilize data visualization tools to communicate findings effectively.
Troubleshoot data issues and conduct root cause analysis.
Identify and contribute to team development initiatives.

Requirements

Bachelor's degree in Mathematics, Statistics, or a relevant technical field.
Minimum of 5 years experience in analytics as a Data Modeler, Data Analyst or similar role in the Finance domain.
Advanced knowledge of SQL, Looker Studio, Data Modelling, and Big Query.
Statistical knowledge and experience with NoSQL (preferably MongoDB) and DBT or similar tools.
Fluent in English; French is good to have.

Work-Life Balance Benefits

Flexible working hours
Remote work options
Supportive company culture

Benefits

Generous vacation policies
Professional development opportunities
Collaborative team environment

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Full Details of Job Post

We are seeking a detail-oriented and analytical Data Analyst to join our Financial Services team. The ideal candidate will play a crucial role in interpreting data, analyzing results, and providing insights to support strategic business decisions. The position requires a blend of technical expertise, statistical and analytical knowledge, and effective communication skills.

About Your Role:

Create conceptual, logical, and physical data models to meet the needs of various business processes. Ensure data models are scalable, maintainable, and flexible to meet evolving business requirements.
Optimize data model performance by analyzing and refining database designs and queries.
Collaborate with data architects, data engineers, data product team and business analysts to integrate data across different sources.
Maintain data documentation, including data models, data dictionaries, metadata, and data lineage to ensure clear communication and understanding among stakeholders.
Develop, implement, and maintain business intelligence solutions to support decision-making processes.
Work closely with business stakeholders to understand their data needs and translate them into technical requirements for data analysis
Provide support and guidance to data analysts and other team members on data-related issues.
Utilize data visualization tools (preferably Looker Studio) to communicate findings effectively to stakeholders to make data-informed decisions.
Expertise in SQL and experience working with large-scale data sets on cloud platforms such as GCP Big Query and DBT.
Troubleshoot data issues and conduct root cause analysis when reporting data is in question.
Excellent presentation and communication skills.
Proactively identify and contribute with team development initiatives, and supporting junior members

Qualifications:

Minimum qualifications
Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience.
A minimum experience of 5 years in analytics as a Data Modeler, Data Analyst or similar role in Finance domain.
Language: English Fluent), French Good to have)
Required Technical Skills:
Advance SQL knowledge Looker Studio
Data Modelling
Big Query
Statistical knowledge
NoSQL Preferably MongoDB DBT or similar tools
Good to have:
Certification in data analysis or related fields.
Big Data experience is a big PLUS Spark, Dataproc, etc.) Python, including libraries such as Pandas and scikit-learn Knowledge of machine learning techniques and tools.