Lead Data Engineer at Equity Bank

Description

THE ROLE PURPOSE

Understand multiple banking databases and table structures; create a complete data map and documentation. Design and implement efficient SQL queries and Python scripts to extract, clean, and transform data for analytics, ML and AI. Build automated ETL/ELT pipelines with data quality checks and monitoring. Deliver curated, analysis-ready datasets and maintain data lineage and governance compliance. 

the KEY responsibilities

• Understand and document multiple banking databases, schemas, and table relationships to create a comprehensive data map. 

• Write efficient SQL queries and Python scripts to extract, clean, and transform data into analysis-ready datasets. 

• Design and maintain automated ETL/ELT pipelines with data quality checks, monitoring, and error handling. 

• Collaborate with Data Scientists, Risk, and Analytics teams to deliver curated datasets for credit scoring and reporting. 

• Ensure compliance with data governance, security standards, and regulatory requirements for PII handling. 

• Optimize query performance and pipeline efficiency for large-scale, high-volume banking data. 

• Maintain clear documentation of data lineage, transformations, and business rules for audit readiness. 

CORE  ACCOUNTABILITIES AND DELIVERABLES

• Build and maintain reliable data pipelines to extract, transform, and load data from multiple banking systems into curated, analysis-ready datasets. 

• Ensure data quality, integrity, and compliance with governance standards, including secure handling of PII and audit-ready documentation. 

• Optimize SQL queries and Python workflows for performance and scalability across large, complex datasets. 

• Deliver automated ETL processes, data marts, and clear documentation to enable analytics, credit scoring, and reporting teams. 

Qualifications

Professional Experience Levels 

• Lead ML Data Engineer: 5+ years of progressive experience in designing and implementing data solutions, including SQL-based extraction, Python-driven pipelines, and data architecture for analytics and machine learning.  

Industry Exposure 

• Experience in Banking, Fintech, or Digital Lending environments is highly desirable 

Must-Have –  

• A bachelor’s Degree, Diploma, or professional certification in Computer Science, Software Engineering, Information Technology, or a closely related field. 

Technical Competencies: 

• Expertise in SQL (complex joins, optimization) and Python for data wrangling and automation. 

• Strong understanding of data modeling, ETL/ELT processes, and pipeline orchestration tools. 

• Ability to troubleshoot performance issues and ensure data quality and integrity. 

 Leadership/Soft Skills: 

• Excellent problem-solving and critical thinking abilities, with a structured approach to troubleshooting and solution design. 

• Strong verbal and written communication skills, with a focus on clear documentation, code readability, and stakeholder engagement. 

• Demonstrated ownership and accountability, consistently delivering high-quality outputs and taking initiative to resolve blockers. 

• Flexible and adaptable in fast-paced, dynamic environments, able to shift priorities and handle ambiguity effectively. 

• Proven ability to collaborate within cross-functional teams, fostering a positive team culture and sharing knowledge across disciplines. 

Apply

https://equitybank.taleo.net/careersection/ext_new/jobdetail.ftl?job=2600003E&tz=GMT%2B03%3A00&tzname=Africa%2FNairobi