INTL-Data Engineer

Insight Global is seeking a Senior Data Engineesr for one of our largest clients nearshore. This individual will be a part of the centralized Data Engineering team, where all data needs go through across the entire organization. This team supports all data warehousing and analytics needs, working closely with the Enterprise Data & Insights team who builds visualizations and analytics off the data that the data engineering team has built. This individual will contribute to development across the full software development lifecycle - from requirements gathering through deployment in all aspects of Data Warehousing, including ETL, data modeling, analytics, and reporting. They will design components for Data Warehouse technologies both on-prem and cloud environments, troubleshoot and support code deployment, and resolve code concerns for best practices, security, and code styles. Current technical gaps in the team include capabilities around Azure, Informatica, Snowflake and DevOps Automation, therefore this individual will have to serve as a mentor if needed in these areas.

• 5+ years of Data Engineering experience building enterprise applications, system integrations, web services, and scalable data solutions.

• Strong expertise in Python, SQL, and Data Engineering fundamentals, including ETL/ELT development, data modeling, data pipelines, and Spark/PySpark.

• Advanced Snowflake experience, including data warehousing, optimization, data integration, and analytics (Snowflake is the primary enterprise data platform).

• Hands-on experience with ETL and data integration tools, preferably Informatica (IDMC/IICS), FiveTran, and HVR, including replication and Change Data Capture (CDC) solutions.

• Strong Microsoft Azure experience, including cloud-based data architectures, integrations, and enterprise data platforms.

• Experience with GitHub and CI/CD pipeline development to support automated deployment, version control, and DataOps practices.

• Hands-on experience building AI-powered solutions and agents using tools such as Copilot Studio, Claude, Databricks Genie, or similar AI platforms.

• Experience with Generative AI technologies, including Retrieval-Augmented Generation (RAG), vector databases, embeddings, enterprise search, and AI workflow orchestration.

• Experience integrating AI agents and data platforms with Databricks, Snowflake, SharePoint, Microsoft Teams, REST APIs, and other enterprise systems.

• Knowledge of Azure OpenAI, Azure AI Foundry, and enterprise AI architecture patterns for scalable AI-enabled solutions.

• Experience developing workflow automation, agent orchestration, and self-service analytics solutions that improve productivity and business outcomes.

• Exposure to Oracle and Linux environments supporting enterprise data engineering and integration initiatives. * Experience enabling Data Engineering teams through AI-powered assistants, copilots, and self-service analytics platforms.

• Experience supporting enterprise AI adoption and modernization initiatives within large-scale data environments.