Senior Data Architect

Our Client…

Our client focuses on revolutionizing fraud prevention and protecting digital transactions through advanced machine learning and behavioral intelligence technologies.

They provide innovative solutions that help financial institutions and online businesses safeguard their digital assets while building customer trust. Their platform analyzes vast amounts of data to identify fraudulent activities in real time by creating complex behavioral profiles for users.

With a team of cybersecurity and data analysis experts, our client continuously adapts to new challenges in the fraud landscape. They emphasize a culture of collaboration and openness, striving to create a safer digital world for everyone.

Is looking for: Senior Data Architect

As a Senior Data Architect, you will play a pivotal role in designing and maintaining a robust data infrastructure that underpins our data-driven initiatives and advanced analytics. Your expertise will be essential in collaborating with data analysts, scientists, and engineering teams to ensure that our data is accurate, accessible, and actionable, ultimately enhancing our product offerings. Your contributions will empower the organization to confidently achieve its business goals through insightful data analysis.

Key Responsibilities

Data Lake Development:

• Design and maintain the infrastructure for storing structured and semi-structured data within a Data Lake.
• Oversee the configuration of AWS infrastructure and services related to the Data Lake.
• Automate data ingestion processes, ETL workflows, and maintenance tasks.
• Develop a consolidated data layer for analysis and reporting purposes.

Data Quality Assurance:

• Ensure high standards of data quality and integrity across all sources and pipelines.
• Implement monitoring systems to quickly identify and resolve data issues.

Performance Enhancement:

• Optimize workflows for data processing to improve performance and efficiency.
• Identify bottlenecks and ensure scalability of data pipelines as data volumes grow.

Data Security Compliance:

• Ensure adherence to relevant data protection regulations and standards.
• Implement security measures to protect sensitive information.

Collaboration & Support:

• Work closely with analysts and scientists to understand their data requirements and ensure availability.
• Provide guidance on best practices in data engineering, analysis, and machine learning tasks.

Reporting & Analysis:

• Create automated reports featuring qualitative and quantitative metrics along with visualizations.
• Conduct exploratory analyses to derive insights and statistical interpretations from the data.

Feature Prototyping & Validation:

•  Prototype new features aimed at enhancing fraud detection capabilities.
•  Validate prototypes through well-designed experiments measuring relevant statistical metrics.

Qualifications

•  Proven track record in developing data storage infrastructure (5+ years).
•  Proficiency in SQL, Python, PySpark, Iceberg, Terraform, AWS services (IAM, S3, Glue, Lambda, EMR), Git, GitLab CI/CD.
•  Experience with relational, column-oriented, and NoSQL database design.
•  Familiarity with statistical metrics used in data analysis (e.g., recall and precision).
•  Strong skills in creating data visualizations (e.g., using matplotlib/seaborn/plotly).
•  Expertise in building and maintaining ETL processes and data pipelines.
•  Ability to interpret non-technical requirements for effective reporting and analysis aligned with product needs.
•  A keen interest in extending beyond engineering into data analysis.
•  Excellent problem-solving abilities with a strong attention to detail.
•  Effective communication skills in English.

If you are excited about leveraging your expertise in a dynamic team environment that is committed to making a significant impact in the field of cybersecurity through innovative solutions, we encourage you to apply.