Lead Engineer, Data & Integration

Role Overview We are seeking an experienced Data Engineer with strong expertise in cloud data warehousing, iPaaS integrations, and modern ETL/ELT pipeline development. The ideal candidate will design scalable data platforms, build high-quality data pipelines, and ensure data governance, quality, and security across the organization. Key Responsibilities Design, develop, and maintain ETL/ELT pipelines for data ingestion, transformation, and integration across multiple systems. Work with Snowflake or similar cloud data warehouse platforms to design schemas, optimize performance, and manage data workflows. Utilize SnapLogic or similar iPaaS tools to integrate applications, APIs, and data sources. Build and orchestrate pipelines using Snowpipe, Streams, Tasks, and other Snowflake automation features. Develop high-performance SQL using Snowflake SQL for transformations, modeling, and validation. Implement data modeling, schema design, metadata management, and scalable warehouse structures. Integrate with APIs using REST, JSON/XML processing, and manage API-based ingestion. Ensure end-to-end source-to-target mapping (STTM), data quality checks, validation, and data governance compliance. Apply data security, access control, and encryption standards across data systems. Build workflow orchestration and automation for pipelines using cloud data tools. Leverage Python for data transformation, automation, and integration tasks. Manage DevOps for data, including CI/CD pipelines, version control, and environment management. Implement logging, monitoring, error handling, and recovery strategies for pipelines and integrations. Collaborate with cross-functional teams to support analytics, reporting, and business use cases. Required Skills & Experience Strong experience in Snowflake or similar cloud data platform (BigQuery, Redshift, Databricks). Hands-on experience with iPaaS solutions such as SnapLogic, Boomi, Mulesoft, or Informatica Cloud. Expertise in ETL/ELT pipelines, data integration, and cloud-native pipeline orchestration. Advanced proficiency in SQL and Snowflake SQL. Experience with Snowpipe, Streams, Tasks, and other Snowflake automation components. Strong knowledge of data modeling, schema design, metadata management, and data lifecycle management. Experience with API integrations, REST APIs, JSON/XML, and automation frameworks. Proficiency in Python for scripting and data workflows. Understanding of data governance, data quality, data validation, and security standards. Experience with DevOps for data, including CI/CD, code repositories, testing automation, and workflow automation. Strong debugging, performance tuning, and error-handling skills. Preferred Qualifications Experience with cloud platforms (AWS, Azure, or GCP). Familiarity with orchestration tools such as Airflow, Prefect, Dagster, or Control-M. Knowledge of integration patterns and microservices-based architecture. Skills: data governance,data,integration,management,sql,automation,snowflake