Job Vacancies at CRDB Bank June 2026

Table of Contents

Job Vacancies at CRDB Bank June 2026, CRDB Bank is dedicated to upholding Sustainability and ESG practices and encourage applicants who share this commitment. The Bank also promotes an inclusive workplace, hence applications from women and individual with disabilities are encouraged.

It is important to note that CRDB Bank does not charge any fees for the application or recruitment process, and any requests for payment should be disregarded as they do not represent the bank’s practices.

1: MANAGER MARKET RESEARCH AND INSIGHT Number of openings: 1

Job Purpose

The Manager – Market Research & Insights is responsible for leading the Bank’s market and customer research initiatives to identify growth opportunities, understand customer behaviour, and assess competitive and market dynamics.

The role serves as the “voice of the customer” and emerging trends identifier, with a strong ability to translate complex qualitative and quantitative data into actionable insights that drive product innovation, digital ecosystem development, and enhanced customer experience.

Principle Responsibilities

Lead research initiatives to conduct gap analysis and identify areas for improvement across both existing and newly launched products, services, and features.
Assess customer adoption, satisfaction levels, and value realization to inform product and service optimization.
Monitor, analyse, and forecast industry, consumer, and digital banking trends, including emerging fintech developments and regulatory changes.
Identify market opportunities, threats, and unmet customer needs to inform business, digital, and innovation strategies.
Track market dynamics and emerging competitive threats to support strategic decision‑making.
Develop customer personas, behavioural segments, and end‑to‑end journey maps using demographic, behavioural, and socioeconomic data.
Generate deep customer insights to guide lifecycle marketing, product development, service design, and customer experience initiatives.
Conduct regular competitor benchmarking on pricing, service standards, customer value propositions, and digital platform capabilities.
Analyse competitor movements and offerings to inform positioning and differentiation strategies.
Design and execute research experiments and studies with rigor, ensuring data accuracy, integrity, and reliability.
Select and apply appropriate research methodologies based on study objectives, including focus groups, mystery shopping, surveys, and Net Promoter Score (NPS) studies.
Analyse and interpret complex research and experimental datasets to identify patterns, validate hypotheses, and derive actionable insights.
Translate analytical outcomes into clear business implications, recommendations, and decision support materials.
Present research findings, insights, and project progress at internal stage‑gate reviews and to cross‑functional stakeholders, clearly articulating risks, opportunities, proposed solutions, and commercial impact.
Ensure all research activities comply with internal brand standards, ethical research practices, and data privacy and protection regulations.
Maintain strong governance over research processes, methodologies, and outputs to ensure the credibility, consistency, and reliability of insights
Lead talent identification, mentoring, and skills development while ensuring SMART KPIs are clearly defined, issued, and consistently monitored for all unit staff.
Drive performance reviews and effective feedback processes alongside fostering strong staff engagement and team motivation within the unit.
Maintain strong relationships with business partners while leading contract negotiations and management to ensure mutual benefits, supported by solid research expertise and experience.

Qualifications Required

Bachelor’s degree in Banking, Finance, Statistics, Marketing, Economics, or a related field.
MBA or Master’s degree in a relevant discipline is highly preferred.
Minimum of 5 years’ experience in market research, customer insights, or analytics roles.
Experience within a financial institution, digital business, or specialized research agency is strongly preferred.
Strong ability to produce accurate and reliable market forecasts and insight‑driven recommendations.
Advanced research, analytical, and problem‑solving skills.
Expertise in statistical and analytical tools such as SPSS, SAS, R, and/or similar platforms.
Proficiency in data visualization tools such as Tableau or Power BI.
Financial Acumen: Strong understanding of banking operations, financial products, market structures, and industry trends.
Communication & Storytelling: Excellent ability to translate complex data into compelling, executive‑ready insights and narratives.
Apply strategic thinking and innovation portfolio management to drive forward-looking initiatives and prioritize impactful opportunities.
Engage and influence stakeholders effectively while making sound decisions under uncertainty.

2: LEGAL COUNSEL-COMMERCIAL Number of openings: 1

Job Purpose

The Legal Counsel Commercial Contracts is responsible for providing legal support on all commercial contractual matters of the Bank. The role focuses on drafting, reviewing, negotiating, and managing commercial agreements to ensure compliance with applicable laws, regulatory requirements, and internal policies, while safeguarding the Bank’s legal and commercial interests. The position supports business units by identifying and mitigating legal risks, advising on contractual obligations, and contributing to sound governance and risk management in commercial transactions

Principle Responsibilities

Draft, review and negotiate a variety of contracts including general contracts and commercial contracts as assigned to ensure all contracts protect the Bank’s legal, financial, and reputational interests.
Provide practical legal advice to business units on commercial transactions, and strategic partnerships by working closely with stakeholders to support projects, advising on contractual obligations, risks, liabilities, and remedies throughout the project lifecycle, and supporting product development and project teams on contractual and legal structuring in line with business objectives, regulatory requirements, and the Bank’s risk management framework.
Lead and manage negotiations with external parties to achieve favorable terms and mitigate risks. Act as a point of contact for internal stakeholders during contract negotiations and other legal related queries.
Identify and address legal risks in contracts. Develop strategies to mitigate risks and resolve contractual disputes or ambiguities.
Ensure contracts comply with applicable laws, regulations and internal policies. Provide legal advice to business teams on contract -related matters, including regulatory compliance.
Develop and update contract management policies, procedures and templates to reflect best practices. Conduct training sessions for stakeholders on contract management, compliance and negotiation strategies.
Collaborate with internal teams (Business Units), including to address contract related queries. Act as a liaison between the legal department and external parties, such as International Banks, Local Banks, Government and its Agencies.
Develop, maintain, and periodically review standardized contract templates for use across the Bank, ensuring they remain current, legally compliant, and aligned with regulatory requirements and the Bank’s policies.
Provide proactive legal support to business units in managing and resolving contractual disputes, claims, and disagreements with counterparties to mitigate issues before escalation.

Qualifications Required

Bachelor’s degree in law (LL. B)
Post Graduate Diploma in Legal Practice
5 years of experience in the legal department in a reputable bank or law firm
Experience in drafting, reviewing, and negotiating commercial contracts for a bank.
Knowledge of regulatory frameworks applicable to financial institutions and banking laws
Experience in providing legal advisory services.
Strong negotiation, stakeholder management, and influencing skills.
Proven ability to manage multiple projects and deadlines in a fast-paced environment.
Strong analytical and problem-solving skills with the ability to interpret complex legal issues.
High level of integrity and professional ethics in handling sensitive information.
Effective communication skills across diverse stakeholder groups.

3. SENIOR DATA ENGINEER Number of openings: 1

Job Purpose

The Senior Data Engineer is responsible for designing, building, and maintaining the scalable data pipelines and ingestion frameworks that power the Digital Banking department. This role focuses on translating disparate, high-volume raw data streams—from mobile apps, internet banking portals, and payment gateways—into structured, clean, and highly optimized data stores.

The Senior Data Engineer ensures that data is consistently available, accurate, and structured to support real-time reporting, advanced business intelligence, and production-ready machine learning models.

Principle Responsibilities

Design, implement, and optimize scalable batch and real-time data ingestion pipelines using distributed computing frameworks like PySpark.
Build and maintain resilient data lakes and warehousing environments, managing storage formats (e.g., Parquet, Delta) and metadata cataloging systems such as a Hive Metastore backed by PostgreSQL or object storage.
Structure and partition large datasets to ensure low-latency query performance for downstream consumers (BI Analysts and Data Scientists).
Implement strict data contract definitions, schema registries, and quality validation checks within pipelines to catch upstream system changes before they break downstream models or reports.
Ensure data pipelines adhere to strict banking data privacy regulations, masking sensitive customer details, managing access control levels, and archiving historical logs securely.
Maintain a highly transparent, clear data catalog mapping out data lineage from core systems to final analytics tables.
Work to deploy data pipelines via containerized environments (Docker/Kubernetes).
Serve as the primary technical point of contact for the BI Team and Data Science Team, translating their business analytics requirements into optimized backend data assets.
Enforce clean, modular, and optimized SQL and Python coding standards for data engineering, ensuring thorough version control (Git) and documentation.

Qualifications Required

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science, Statistics, Mathematics, or any related field.
Minimum of 3 years of professional experience as a Data Engineer or Core Database Developer, with a proven track record of managing production-grade data pipelines.
Advanced, hands-on experience using PySpark/Spark to extract, transform, and load massive, complex datasets.
Deep understanding of managing decoupled data environments, file storage types (Parquet etc), and metadata catalogs (Hive Metastore).
Expert-level proficiency in writing and optimizing complex queries, indexing, and modeling data structures within relational engines (e.g., PostgreSQL, Oracle).
Strong familiarity with container tools (Docker) and modern data orchestration workflows (e.g., Apache Airflow or cron-based job scheduling).
Dedication to automation, building resilient architectures that can recover from network timeouts, api failures, or source data spikes without manual intervention.
An obsessive eye for identifying performance bottlenecks in queries and pipeline steps to minimize computing costs and execution time.
Excellent technical communication skills, allowing for seamless collaboration with data consumers to understand exactly how the data needs to be shaped.
Flexible and adoptive to market dynamics and experimentation.
Customer‑centric mindset.
Self-driven and problem‑solving skills.

4: SENIOR DIGITAL DATA SCIENTIST Number of openings 1

Job Purpose

The Senior Data Scientist is the principal technical architect and hands-on lead for the data science team. This role is responsible for designing, building and deploying highly scalable machine learning models that optimize digital banking products, predict customer behavior and manage risk.

The Senior Data Scientist bridges the gap between pure research and production engineering, ensuring the team’s code is robust, automated and seamlessly integrated into live banking workflows.

Principle Responsibilities

Design, train and validate complex predictive and prescriptive models (e.g., real-time credit scoring algorithms, predictive churn models and recommendation engines).
Build scalable, repeatable feature engineering pipelines that process large volumes of digital banking log data, utilizing tools like PySpark and SQL.
Package and containerize models (using Docker) and work with system architects to deploy them as low-latency microservices/APIs into production.
Establish and enforce best practices for version control (Git), code modularity, documentation and automated testing across the data science pipeline.
Peer-review and audit the mathematical frameworks and assumptions made in models built by junior data scientists to prevent overfitting, bias or data leakage.
Actively mentor Junior Data Scientists, guiding them through complex algorithmic challenges, feature selection techniques and hyperparameter tuning.
Stay at the forefront of AI/ML trends, assessing how new techniques (e.g., Large Language Models, advanced graph analytics for fraud detection) can be applied to digital banking.

Qualifications Required

Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
Minimum of 4 years of professional experience as a Data Scientist, with a documented history of shipping machine learning models directly into production environments.
Expert-level Python skills, with fluency in the data science stack (Scikit-Learn, Pandas, NumPy).
Practical experience processing high-velocity transaction data using distributed computing frameworks, specifically PySpark/Spark.
Strong proficiency with containerization (Docker) and setting up persistent metadata environments (e.g., interacting with a Hive Metastore backed by relational or object storage).
Advanced SQL skills optimized for writing complex queries over large data stores (e.g., PostgreSQL oracle).
The ability to look at a complex banking problem and architect an algorithmic solution.
Ability to manage high-performing technical minds, fostering a collaborative, non-siloed engineering culture.

Flexible and adoptive to market dynamics and experimentation.
Customer‑centric mindset.
Self-driven and problem‑solving skills.

5: MLOPS ENGINEERS Number of openings 1

Job Purpose

The MLOps Engineering Manager is an engineering role responsible for the infrastructure, automation, and pipelines that power both Data Engineering and Machine Learning operations. This role leads the design, deployment, and maintenance of scalable data platforms (e.g., Hive Metastores, PostgreSQL, MinIO/S3 architectures) and robust MLOps lifecycles.

The Manager ensures that raw digital banking data flows seamlessly to the BI/Data Science teams, and that predictive models are deployed into production via automated, low-latency, and secure CI/CD pipelines.

Principle Responsibilities

Infrastructure Architecture & Data Engineering Leadership.
Oversee the architecture and optimization of the department’s persistent data platforms, including distributed object storage, Hive Metastores, and relational databases.
Work with the Senior Data Engineer to ensure that robust, containerized data pipelines (e.g., PySpark workflows running on Docker/Kubernetes) are optimized for low-latency transaction processing.
Manage cluster resources, storage scaling, and compute environments to balance performance with infrastructure costs.
MLOps Strategy & Automated CI/CD Lifecycles.

Design and enforce automated CI/CD pipelines for deploying Machine Learning models as highly available, production-grade microservices/APIs.

Implement automated infrastructure to track model telemetry, monitoring API latency, prediction accuracy, and data/concept drift in real-time.
Own the orchestration and containerization strategy (Docker, Kubernetes) to guarantee that environments match perfectly from a data scientist’s local sandbox to the production cluster.
Act as the critical operational bridge linking the Data Science Manager (who designs the models) and the BI Manager (who consumes the data assets) with the bank’s core Core Banking IT and Security teams.

Qualifications Required

Bachelor’s in Computer Science, Information Technology, Software Engineering, Data Engineering, or a related technical field.
Minimum of 5 years of experience spanning DevOps, Cloud/Infrastructure Engineering, Data Engineering, or MLOps with at least 1–2 years in a lead or managerial position.
Proficiency with Docker and Kubernetes for scaling data and model workloads.
Strong hands-on experience setting up, tuning, and decoupling data architectures using Hive Metastores, PostgreSQL, and high-performance object storage.
Deep familiarity with modern deployment and tracking pipelines (e.g., Git Actions or cloud-native equivalents etc.).
Strong mastery of Python, shell scripting, and distributed processing environments using PySpark.
The ability to design modular, decoupled data architectures that prevent systemic bottlenecks.
A strong “infrastructure as code” and automation-first mindset; a refusal to accept manual, fragile deployment steps.
Ability to negotiate infrastructure access, security clearances, and server resource allocations with centralized corporate IT divisions.
Flexible and adoptive to market dynamics and experimentation.
Customer‑centric mindset.
Self-driven and problem‑solving skills.

CRDB Commitment

CRDB Bank is dedicated to upholding Sustainability and ESG practices and encourage applicants who share this commitment. The Bank also promotes an inclusive workplace, hence applications from women and individual with disabilities are encouraged.

Only Shortlisted Candidates will be Contacted.

Deadline: 2026-06-30