Jobs at Billigence

Lead end-to-end technical delivery of enterprise data and analytics solutions across strategic transformation programmes. Translate complex business requirements into scalable architectures, data models, integration frameworks, and ETL requirements. Produce technical designs and solution blueprints, ensure architecture governance compliance, manage technical risks and dependencies, coordinate vendors and cross-functional teams, support programme planning, and drive stakeholder adoption while maintaining Agile delivery standards.

Designs enterprise data architectures, conceptual, logical and physical data models, integration patterns, data flows, and technical blueprints. Translates business requirements into scalable, governed data solutions while collaborating with engineering, analytics, technology, stakeholders, vendors, and delivery partners. Supports ETL/ELT requirements, architecture governance, technical reviews, risk management, and delivery of maintainable cloud data platforms within a major transformation programme.

Generates new business opportunities for a data consultancy through research, outbound outreach, lead qualification, relationship building, and meeting scheduling. Maintains CRM records, supports pipeline development, engages data and technology stakeholders, and collaborates with senior sales and consulting teams. The role offers an entry point into technology sales with potential progression to Account Executive or Account Management positions.

Design, build, and optimise cloud-based data pipelines, ETL/ELT processes and enterprise data platforms for an insurance client. Integrate multiple source systems, ensure data quality and performance, support data modelling and transformation, and collaborate with stakeholders using Agile practices.

The Data Management Lead will oversee data management initiatives for AI transformation, focusing on data quality, governance, and stakeholder engagement while collaborating with various teams.

The Data Management Lead will oversee initiatives to improve workforce data quality, governance, and operational management, collaborating with multiple teams to establish standards and support data strategy.

Design and maintain data architectures, build data pipelines, and communicate with stakeholders to enhance data reliability and quality.

Conduct outbound prospecting (calls, email, LinkedIn) to generate qualified meetings for BDMs/AMs across APAC; support event outreach and on-site activities; maintain CRM data; qualify prospects for Snowflake, AI, data governance, and analytics opportunities; hit weekly/monthly outreach targets and progress into BDM or AM roles.

Design, develop, test, and maintain software using languages like Java, Python, C++, or Ruby. Collaborate with cross-functional teams, perform code reviews, debug and troubleshoot systems, produce documentation, stay current with technologies, and mentor junior engineers.

The DWH Developer will design and build data warehouse solutions, set up cloud infrastructure, and provide data-driven insights while communicating with stakeholders.

Design, develop, and maintain scalable Java backend applications and secure REST APIs using Spring Boot, microservices, and event-driven architecture. Build cloud-native data solutions, implement automated testing and CI/CD, manage Kubernetes deployments and production releases, and provide on-call support. Lead incident resolution, root cause analysis, observability, performance optimization, code reviews, mentoring, documentation, and continuous improvement.

Generates new business and manages client relationships for data and analytics consulting solutions in Saudi Arabia. Responsibilities include prospecting, networking, sales meetings, proposals, pipeline management in HubSpot, partner development, and representing the company at industry events. The role requires Arabic and English fluency, strong communication skills, commercial interest, and enthusiasm for technology, data, AI, and consulting. Client-site travel is required, with hybrid or remote work options available.

Own data quality, stewardship and documentation across assigned domains: profile and cleanse data, define validations, maintain catalogues and lineage, run governance controls, and liaise between engineering and business stakeholders.

Design and build end-to-end data pipelines on Snowflake using a medallion architecture; develop dbt transformations and tests; implement automated data validations; create Streamlit UIs for user inputs and checks; prepare Power BI reporting outputs; document and hand over solutions to clients while collaborating with stakeholders.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

Lead design and delivery of cloud data platform solutions for banking clients. Own solution design, data modelling, ETL/CI-CD, SQL development, stakeholder engagement, and lead technical project delivery.

The role involves transforming raw data, building data models and Power BI dashboards, maintaining data pipelines, and collaborating with PMs to meet business requirements.

Design and deliver scalable cloud data pipelines, ETL/ELT and data warehousing solutions. Work hands-on in Snowflake, Databricks and cloud platforms, translate business requirements into technical designs, optimise queries, and engage with stakeholders across client projects and internal initiatives.

Lead requirements elicitation and analysis for BI, data and digital transformation projects. Document business, functional, non-functional and data requirements; run workshops; produce BRDs, user stories, process maps and acceptance criteria. Liaise between stakeholders and technical teams, support solution design, UAT, requirements traceability, change management and project delivery.

The Senior Full Stack Developer will design and maintain web applications using React.js and Java, manage cloud infrastructure on AWS/Azure, and optimize microservices. They will collaborate with teams to enhance API performance and troubleshoot full-stack issues.