• Administer a cloud data warehouse platform (e.g., Snowflake or similar), including roles/permissions, performance tuning, security, & cost governance • Utilize Git for version control & collaboration throughout the development lifecycle • Help design scalable, reliable, & secure data architectures & models

Role Description At Coforge, we are looking for a Senior Data Modeller (#22048) with the following profile. - Design and maintain enterprise data models (conceptual, logical, and physical models) - Develop dimensional data models (facts, dimensions, star schemas) optimized for Snowflake and Power BI consumption - Define data entities, relationships, hierarchies, grain, naming standards, and reusable structures - Collaborate closely with Business Analysts, Data Engineers, Analytics Engineers, and QA/SDET teams to ensure alignment across data solutions - Ensure consistency of core business metrics and establish a single source of truth - Align business definitions with scalable data structures to support reliable analytics and reporting - Support the consolidation of data into a centralized cloud-native platform (Snowflake on AWS) - Design data models that enable decision-making across underwriting, claims, finance, and operations - Ensure data models are optimized for performance, scalability, and usability Qualifications - 7–10+ years of experience in Data Modelling and Data Warehousing environments - Strong expertise in data modelling (DW/DM concepts) and dimensional modelling (star schema, facts, dimensions) - Advanced proficiency in SQL - Hands-on experience with Snowflake - Experience with cloud data platforms (AWS or Azure) - Experience working with BI tools such as Power BI or similar - Strong understanding of ETL/ELT pipelines and end-to-end data flows - Knowledge of data performance optimization and scalability best practices - Ability to translate business concepts into scalable and reusable data models - Strong focus on data consistency, structure, and usability - Experience working in cross-functional data teams - Advanced or fluent English communication skills (mandatory) Preferred Qualifications - Experience in the insurance domain (claims, policies, underwriting, risk) - Hands-on experience with DBT (Data Build Tool) - Familiarity with modern cloud-native data architectures - Experience supporting enterprise data transformation initiatives Location LATAM (open to all countries in the region) Work Model Remote for legal residents in Latam Published on 7-7-2026 Company Description At Coforge, we hire professionals based solely on their skills and qualifications, without discrimination based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Role Description Seeking a Data Engineer responsible for designing, developing, and maintaining scalable enterprise data pipelines supporting advanced fraud analytics. The candidate will manage ingestion, transformation, quality control, and optimization of structured and unstructured data across cloud-based analytics platforms. - Demonstrate the ability to design, build, and maintain scalable ETL pipelines across diverse data sources. - Apply strong SQL and Python skills, or equivalent technologies, to ingest and transform data from flat files, JSON, XML, Excel, APIs, graph databases, with flexibility to adapt to additional formats and sources as needed. - Possess experience loading, managing, and optimizing data within platforms such as Databricks Unity Catalog and SQL Server managed instances, including work with streaming and batch ingestion frameworks and modern Lakehouse architecture. - Exhibit strong capabilities in implementing standard quality control processes to ensure data quality, lineage, reliability, and performance while collaborating effectively with cross‑functional teams. - Have familiarity with data governance, data quality, and data management practices consistent with enterprise data management (EDM) standards. - Experience supporting fraud detection, anomaly detection, or financial oversight analytics environment preferred. Qualifications - Minimum 3 years data engineering experience. - Strong SQL skills. - Strong Python programming. - Experience building ETL pipelines. - Experience with Databricks. - Experience with Azure SQL or SQL Server. - Experience implementing data quality processes. Requirements - Experience with fraud detection analytics. - Experience with streaming data pipelines. - Experience supporting enterprise data governance. Benefits - 401(k) - Dental insurance - Health insurance - Paid time off - Vision insurance Company Description This is a remote position.

• Design, develop, and maintain robust enterprise data warehouse solutions that support data science, artificial intelligence, and business intelligence requirements. • Architect scalable ETL/ELT pipelines to efficiently transform raw data into structured, analytics-ready formats. • Build and manage API integrations, including hands-on API development. • Utilize T-SQL and Azure Data Factory to create, optimize, and manage data integration workflows. • Use Microsoft Fabric notebooks for transformation and orchestration where appropriate, leveraging Lakehouse and Warehouse for supplemental storage. • Ensure high data quality, integrity, and performance through meticulous query tuning and process optimization. • Collaborate with data scientists, software developers, business intelligence teams, and stakeholders to develop and deploy data solutions that meet business needs. • Translate business requirements into technical solutions and coordinate smoothly between engineering and other teams. • Lead the creation of scalable, reliable data models and optimize them for performance and usability. • Drive continuous improvement in data engineering processes and practices to keep them efficient and aligned with industry best practices. • Monitor system performance and proactively implement improvements to maximize efficiency and scalability. • Troubleshoot and resolve data-related issues to ensure reliable data delivery.