Build and maintain robust data pipelines processing large volumes of data
Update and optimise our data platform for speed, scalability and cost
Coordinate with different functional teams to understand and meet their data needs
Moniepoint Inc. is Africa’s all-in-one financial platform, helping 20 million businesses and individuals access seamless payments, banking, credit, cross-border, and business management tools each month. As Nigeria’s largest merchant acquirer, we process over $250 billion annually and prioritize employee well-being with a learning-focused culture.
Own and build client-facing data transformations faster and more scalably, leveraging AI to accelerate and document work.
Design and evolve data integrity tests in collaboration with Engineering and Customer Success to catch issues early.
Partner with Customer Success to understand data needs, troubleshoot issues, and optimize models and pipelines.
Aleph is an AI-native platform for Financial Planning & Analysis (FP&A), solving data integration and decision-making challenges for finance teams. Founded by technical founders from Stanford and MIT, they are backed by top VCs and work with customers like Webflow and Notion, operating with a remote-first culture across the Americas.
Develop, adjust, and evolve data pipelines using Databricks and PySpark.
Analyze processes migrated from legacy systems (SAS, Hive, Teradata) and make necessary adjustments.
Identify bottlenecks and implement performance improvements and optimizations in pipelines and large-scale data processing.
CI&T helps large companies transform AI potential into real business impact with AI deployment, AI-native execution, and tech-integrated business solutions. With 30 years of experience and 8,000 employees across 25+ countries, we accelerate innovation through expertise in agentic SDLC, application modernization, Data & AI, martech, and business strategy.
Write optimized SQL and Python to turn raw healthcare data into actionable insights.
Build dashboards and reports that drive decisions across product and customer success teams.
Investigate data quality issues and present findings to technical and non-technical audiences.
Clarium builds AI-powered software that helps hospitals cut supply chain waste and focus on patient care. Founded in 2020 and backed by $43M, the company is a high-growth, collaborative team trusted by leading health systems.
Contributes to existing code repositories by extending and maintaining code according to established patterns and conventions.
Builds data pipelines that feed downstream applications, including AI agents, using Google BigQuery and SAP.
Communicates progress, blockers, and technical decisions clearly and consistently with the broader team.
CI&T helps large enterprises transform with AI and technology solutions. With 6,000+ employees across 25+ countries, they foster a collaborative culture focused on innovation and real business impact.
Contributes to existing code repositories following Git best practices and communicating clearly with the team.
Builds data pipelines and develops ETL processes feeding AI agents and downstream applications.
Develops front-end interfaces for internal applications and supports machine learning models for computer vision and forecasting.
We help large enterprises transform the potential of AI into real business impact. We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact.
Develop and maintain data pipelines for data ingestion, transformation, and processing using Python and SQL.
Collaborate with Data Engineers, Analysts, and global stakeholders to deliver effective data solutions.
Apply modern data engineering practices, including Git, CI/CD, and cloud platforms like Azure and Databricks.
They partner with global clients to deliver large-scale digital transformation initiatives through data solutions. They foster a remote, multicultural environment emphasizing technical growth, collaboration, and continuous improvement.
Design, build, and maintain reliable data pipelines using SQL and Python.
Develop and optimize data models in Snowflake or equivalent cloud data warehouses.
Diagnose and resolve data quality issues and support production operations.
Our partner company is seeking a data-focused engineer to build clean, reliable data solutions. They emphasize collaboration, continuous learning, and technical craftsmanship with a remote-first culture.
Lead design, implementation, and optimization of complex enterprise data engineering solutions for scalable, secure data platforms.
Develop advanced data pipelines, integration frameworks, quality processes, and monitoring capabilities across enterprise systems.
Provide technical leadership, mentor engineers, and drive continuous improvement in performance, automation, and operational excellence.
The University of Kansas Health System is a world-class healthcare provider in Kansas City, part of a premier academic medical center. It is driven by commitment to service, continuous improvement, and excellence, with a collaborative culture among physicians, nurses, researchers, and professionals.
Design, develop, and maintain scalable data solutions using Microsoft Azure ecosystem.
Build and optimize ETL/ELT pipelines with Azure Data Factory, Databricks, and Synapse.
Collaborate with stakeholders to turn diverse data sources into trusted, analytics-ready datasets.
Our partner is a company undergoing a large-scale digital transformation initiative. They are looking for an experienced data engineer to work with modern Microsoft Azure data technologies.