• Serve as the internal authority on Snowflake architecture, performance tuning, cost governance, and security (RBAC, data masking, network policies). • Design and maintain a scalable, well-documented warehouse structure including database, schema, and object hierarchy standards. • Drive Snowflake feature adoption — dynamic tables, Snowpark, data sharing, and emerging capabilities. • Own the dbt project end-to-end: modeling conventions, testing strategy, documentation standards, and CI/CD integration. • Establish and enforce a layered modeling approach (staging → intermediate → marts) that downstream teams can trust and self-serve. • Lead the design and operation of data pipelines on Azure, including Azure Data Factory • Ensure reliable, monitored data movement from source systems into Snowflake with clear SLAs and alerting. • Manage, mentor, and grow a team of data engineers — running regular 1:1s, setting performance goals, and building a culture of engineering excellence. • Own hiring, onboarding, and career development for the data engineering function. • Translate business requirements from stakeholders into well-scoped, prioritized engineering work. • Define and enforce organization-wide ETL/ELT best practices, naming conventions, and code review standards. • Champion data quality, observability (e.g., dbt tests), and lineage across the platform. • Proactively identify opportunities for data process improvements and lead initiatives to implement these changes.

• Lead and mentor a team of data engineers, fostering a culture of innovation and continuous improvement. • Design, implement, and optimize data pipelines and ETL processes to support business needs. • Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions. • Ensure data quality, governance, and compliance with industry standards and best practices. • Evaluate and integrate new technologies and tools to enhance data processing capabilities.

• Understanding business requirements and writing code to implement solutions. • Creating data pipelines and managing versioning and change management. • Developing batch or real-time data pipelines. • Logging and instrumentation of pipelines and services. • Ensuring data accuracy, integrity, and compliance through quality control procedures.

Lead Data Engineer Bolivia Job Description: Job Title: Lead Data Engineer Key Skills: Snowflake, Azure Databricks, DBT, Terraform, SQL, ETL/ELT, Azure Cloud, CI/CD, Data Migration, Data Architecture Experience: +8 YOE. Location Bolivia Mode: Remote We at Coforge are hiring Lead Data Engineer (#20978) with the following skill set. Key Responsibilities - Lead and mentor a team of data engineers, ensuring best practices and high-quality deliverables. - Own and drive the end-to-end migration strategy from Snowflake on AWS to Azure Databricks and DBT. - Architect and oversee scalable, secure, and reliable data pipelines and infrastructure in Azure. - Design and implement Infrastructure-as-Code solutions using Terraform and manage CI/CD workflows. - Collaborate with cross-functional stakeholders to align data initiatives with business and technical goals. Required Skills & Qualifications - 8+ years of experience in Data Engineering, including leadership or technical lead experience. - Strong hands-on expertise with Snowflake, Azure Databricks, and DBT. - Deep experience with Terraform and cloud infrastructure automation. - Proven experience leading large-scale cloud data migration projects, preferably AWS to Azure. - Advanced proficiency in SQL, data modeling, and ETL/ELT frameworks. - Strong understanding of scalable data architecture and performance optimization. - Experience with CI/CD pipelines and Git-based version control. - Mandatory experience within the insurance industry and knowledge of insurance data domains. - Excellent communication, stakeholder management, and leadership skills. - Ability to work effectively in fast-paced and collaborative environments. Preferred Skills: - Experience with data governance and observability frameworks. - Knowledge of security and compliance standards related to insurance or financial data. - Familiarity with Kafka, Event Hubs, or real-time data processing solutions. - Experience designing lakehouse architectures and cost-optimization strategies. - Exposure to multi-cloud environments and advanced automation practices. Posted On: 8-05-26 At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.