Design, build, and optimize end-to-end ELT/ETL pipelines into Snowflake, model data for analytics, enforce governance and security, ensure observability and cost controls, and automate deployments via CI/CD and infrastructure-as-code while partnering with analytics, data science, and product teams.
We’re looking for a Snowflake Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions on Snowflake. You’ll partner with data, analytics, and product teams to deliver reliable, secure, and cost-efficient data products that power business decisions. Key Responsibilities Design and implement end-to-end ELT/ETL pipelines into Snowflake from diverse sources (batch and streaming). Model data for analytics use cases (dimensional and data vault) and build reusable data products and marts. Optimize Snowflake performance (warehouse sizing, query tuning, micro-partitioning, clustering, pruning). Implement data ingestion using Snowpipe, tasks, streams, and external stages (S3/ADLS/GCS). Ensure data quality, lineage, and observability (tests, alerts, SLAs, and documentation). Enforce security and governance (RBAC, masking, row-level access, data sharing, audit, compliance). Implement cost controls and monitoring (resource monitors, warehouse policies, storage lifecycle). Collaborate with analytics engineers, data scientists, and business stakeholders to translate requirements into scalable solutions. Automate deployments and environment management via CI/CD and infrastructure-as-code. Maintain standards, patterns, and best practices for Snowflake development. Required Qualifications data engineering (Snowflake-focused for mid-level; 6–8+ for senior). Strong SQL and data modeling skills (star/snowflake schemas, data vault, incremental patterns). Hands-on with core Snowflake capabilities: Virtual Warehouses, Databases/Schemas Stages, Snowpipe, Streams & Tasks Time Travel, Zero-Copy Cloning External tables and file formats
Similar Jobs
Information Technology • Consulting
Lead end-to-end big data development on Azure Databricks: design/implement data ingestion, preparation, integration and operationalization. Hands-on PySpark coding, advanced SQL, DWH and data architecture knowledge; own coding, testing, debugging and deployment. Strong communication required.
Top Skills:
AzureAzure DatabricksData LakeData MartData WarehousePysparkPythonSQL
Information Technology • Consulting
Design and model Neo4j graph database solutions, define graph schemas, and optimize Cypher queries. Integrate Neo4j with Java, develop backend services using Java 8+ and Spring Boot, build REST APIs, and implement CI/CD on Azure (Azure DevOps). Use Git, Maven/Gradle, and application monitoring.
Top Skills:
Application MonitoringAzure App ServicesAzure DevopsAzure SqlAzure StorageAzure VmsCi/CdCypherGitGradleJavaMavenNeo4JNeo4J DriverRest ApisSpring Boot
Information Technology • Consulting
Lead end-to-end big data development on Azure Databricks using PySpark and SQL. Build and operationalize data ingestion, preparation, integration pipelines across data lakes, data warehouses and marts. Own coding, testing, debugging, and deployment while collaborating with stakeholders and communicating technical designs.
Top Skills:
AzureAzure DatabricksData LakeData MartData WarehousePysparkPythonSQL
What you need to know about the Delhi Tech Scene
Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
