Data Engineer

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Data Engineering, Snowflake Data Warehouse Good to have skills : Machine Learning (ML) Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary Lead the architecture, strategy, and delivery of enterprise-scale data platforms on Snowflake. Own technical direction for data modeling, ingestion, performance, security, governance, and developer experience. Mentor engineers and collaborate with stakeholders to deliver robust, scalable, and secure data solutions for analytics, AI/ML, and operational use cases. Roles and responsibilities: Architecture & Strategy Define target data platform architecture (multi-environment, multi-account, integration patterns). Establish technical standards for ELT, dbt/Snowpark, data contracts, and lifecycle management. Lead make/buy/standardize decisions for connectors, CDC/integration tools, orchestration, catalog, and observability. Design and Implement CI/CD pipelines for data engineering workflows Design and Implement Streaming data architectures and Micro-service based architectures Design and implement reliable ingestion and transformation pipelines (batch/streaming) using Snowflake features (Snowpipe, Streams & Tasks, external stages) and orchestration tools (Airflow/ADF). Drive data modeling best practices (dimensional, data vault, wide tables) with versioning, testing, and documentation. Enable CI/CD, environment promotion, automated data quality checks (dbt tests, Great Expectations), and blue-green deployments. Performance, Reliability & Cost Lead workload management, query optimization, clustering, and caching strategies. Implement resource monitors, autosuspend policies, and cost observability dashboards. Own SLA/SLOs for key data products, incident runbooks, lineage-aware impact analysis, and post-incident reviews. Security, Compliance & Sharing Define and enforce RBAC/ABAC, row/column-level security, masking policies, and secrets management. Partner with Security/GRC on auditing, data retention, PII/PHI protection, and regulatory compliance (GDPR/CCPA). Operationalize secure data sharing and cleanroom patterns for internal/external collaboration. Leadership & Influence Serve as principal technical authority for Snowflake mentor engineers and elevate team capability. Collaborate with Product, Analytics, and ML teams to deliver scalable, reusable data products. Author architecture decision records (ADRs), roadmaps, and executive-level technical narratives. Technical experience & Professional attributes: 12+ years in data engineering/architecture 6+ years designing and operating Snowflake at scale (multi-TB warehouses, 1000s of daily jobs).