Data Engineer II: Envestnet Trivandrum

Envestnet is hiring a Data Engineer II for its Trivandrum office on a full‑time hybrid basis. The role focuses on implementing pipelines, transformations, data models, and reusable data products for a next‑generation enterprise data and analytics platform in a secure cloud environment. The engineer will work closely with product, operations, and business teams to modernize ingestion, establish a canonical Common Data Model, and adopt a medallion architecture with Bronze, Silver, and Gold layers.

• Deliver end‑to‑end data and analytics capabilities across data modeling, ingestion, transformation, orchestration, testing, and production support.
• Build scalable, secure, observable, and fault‑tolerant workflows using SQL, Python, PySpark, Snowflake, dbt, Airflow, Spark, and AWS services.
• Develop Bronze, Silver, and Gold layer transformations aligned with medallion architecture and enterprise star‑schema standards.
• Support onboarding of strategic platforms using reusable integration patterns, and contribute to source‑to‑enterprise mappings and Gold‑layer data products.
• Reproduce and validate existing extracts, reports, and datasets by reconciling new platform outputs against current production outputs.
• Implement automated data quality controls, monitoring, alerting, scorecards, and reusable testing libraries.
• Analyze source systems, client data, and business requirements, then translate them into maintainable technical designs.
• Document issues, designs, lineage, solutions, and recommendations for internal and external stakeholders.
• Use AI‑assisted engineering tools responsibly to build, debug, test, and accelerate delivery while maintaining review and quality standards.

• Bachelor's degree in computer science, engineering, information systems, or equivalent practical experience.
• Hands‑on data engineering experience with advanced SQL and Python, plus PySpark or Spark for distributed data processing.
• Experience designing and operating ETL or ELT pipelines, dimensional data models, and production‑grade data workflows.
• Practical experience with Snowflake, dbt, Airflow, and AWS data services in a cloud‑based data platform environment.
• Working knowledge of CI/CD, version control, automated testing, and deployment using GitLab, AWS CodeCommit, or comparable tools.
• Ability to gather and interpret business requirements and deliver in Agile teams using Jira or similar tools.