Responsibilities 
API Integration & Data Extraction 

• Lead the integration of Fenergo APIs to extract relevant KYC and AML data, ensuring seamless connectivity and data flow between systems 

• Design, develop, and maintain scalable data pipelines and ETL processes to support data ingestion from various sources, including databases, APIs, and flat files 

• Ensure robust data extraction processes that maintain data quality and compliance with regulatory requirements 

Data Processing & Pipeline Development 

• Utilize Databricks and Apache Spark to design and implement robust data processing pipelines, ensuring high data quality and performance 

• Work with DataFrames for transforming data and implementing the Medallion Architecture 

• Execute SQL queries for data extraction, manipulation, and complex data operations 

• Join datasets and add fields to reports to provide comprehensive analytical insights 

• Leverage AI tools in Databricks to assist with data workflows and optimization 

• Use notebooks as data transformation pipelines for efficient data processing 

Data Analysis & Interpretation 

• Analyze and interpret complex data sets to identify trends, patterns, and anomalies that can inform business decisions related to client and investor lifecycle management 

• Understand and navigate the data model to ensure accurate data representation and reporting 

• Conduct regular data quality assessments and audits to ensure data integrity and compliance with industry standards 

• Perform root cause analysis to swiftly identify data issues and collaborate with relevant teams to implement effective solutions 

Data Visualisation & Reporting 

• Architect and develop interactive dashboards and reports in Power BI, translating complex data into clear, actionable insights for clients, leadership, and stakeholders 

• Develop and maintain dashboards and reports to provide insights into key performance indicators (KPIs) and operational metrics for KYC/AML processes 

• Create visual representations that highlight critical data points for regular reporting to clients and senior management 

• Ensure reports meet the needs of both technical and non-technical stakeholders 

Collaboration & Stakeholder Management 

• Collaborate with cross-functional teams, including IT, Compliance, Risk Management, business analysts, and senior management, to gather data requirements and deliver strategic insights 

• Engage with clients and internal stakeholders to understand their reporting needs and ensure alignment with business objectives 

• Work closely with KYC/AML operations teams to ensure data solutions support compliance and regulatory requirements 

• Act as a bridge between technical teams and business users, translating complex data concepts into actionable business insights 

Documentation & Governance 

• Maintain comprehensive documentation of data processes, API integrations, data flows, data management processes, and reporting solutions for future reference and compliance 

• Document data governance practices and ensure adherence to data quality best practices 

• Ensure all data handling complies with regulatory standards and internal policies 

Continuous Improvement & Problem-Solving 

• Recommend long-term product solutions to enhance data quality, accessibility, and usability 

• Identify opportunities for process optimization and automation in data workflows 

• Stay up-to-date with industry trends and best practices in data engineering, analysis, and management 

• Proactively identify and resolve data-related issues, ensuring timely and accurate reporting 

• Demonstrate creativity and insightfulness in developing dynamic approaches to complex data challenges 

Quality Assurance 

• Ensure data integrity throughout all pipelines and reporting mechanisms 

• Implement data validation and quality control measures 

• Monitor data processes and implement control mechanisms to ensure reliability 

Skills 

Core Data Engineering Skills (Required): 

• Proficiency in Databricks and Apache Spark for data processing and pipeline development 

• Strong knowledge of Power BI for data visualization and reporting, with ability to create executive-level dashboards 

• Expert-level proficiency in SQL for data querying, manipulation, and complex analytical operations 

• Experience with programming languages such as Python or R for data analysis and automation 

• Strong understanding of data warehousing concepts and ETL processes 

• Knowledge of data modeling concepts and best practices for data management 

• Understanding of the Medallion Architecture and data lakehouse principles 

• Experience working with DataFrames for data transformation 

• Ability to leverage AI tools in Databricks to optimize data workflows 

API & Integration Skills (Required): 

• Strong experience in API integration for data extraction and system connectivity 

• Ability to ensure seamless data flow between multiple systems 

Cloud & Infrastructure (Required): 

• Experience with cloud platforms, particularly Azure or AWS 

• Knowledge of Git connection to Databricks for version control 

• Experience with AWS/Azure and Databricks integration/mounting 

• Understanding of data governance and data quality best practices 

Additional Technical Skills (Preferred): 

• Databricks administration skills 

• Familiarity with machine learning concepts and their application in data analysis 

• Experience with graph data models 

• Understanding of data governance and compliance standards (GDPR, AML regulations, etc.) 

• Knowledge of secure data handling practices