Snowflake DBT Developer with Heavy Databricks-Location

We are seeking a highly skilled Snowflake DBT Developer with extensive hands-on experience in Databricks to design, develop, and optimize modern cloud-based data platforms. The ideal candidate will have strong expertise in building scalable ELT pipelines using dbt, implementing data transformations in Snowflake, and leveraging Databricks (PySpark & Spark SQL) for large-scale data processing., This role requires a strong understanding of data warehousing, cloud-native architectures, performance optimization, and CI/CD best practices. The candidate will work closely with Data Architects, Data Engineers, BI Developers, and Business stakeholders to build reliable, scalable, and high-performance data solutions. Modern data engineering roles increasingly combine Snowflake, dbt, Databricks, SQL, cloud platforms, Git, CI/CD, and data quality practices., * Design, develop, and maintain enterprise-grade ELT pipelines using dbt and Snowflake.

• Build scalable data ingestion and transformation frameworks using Databricks, PySpark, and Spark SQL.

• Develop dimensional models, star schemas, and data marts for analytics and reporting.

• Optimize Snowflake objects including:

• Virtual Warehouses

• Tables

• Materialized Views

• Streams & Tasks

• Clustering Keys

• Query Performance

Build reusable dbt models, macros, snapshots, tests, and documentation.

Develop incremental models and implement CDC (Change Data Capture) patterns.

Process structured and semi-structured data (JSON, Avro, Parquet, XML).

Implement Delta Lake architecture and optimize Spark workloads.

Collaborate with business users to translate requirements into scalable data solutions.

Implement data quality validation, automated testing, and monitoring.

Optimize pipeline performance, cloud costs, and warehouse utilization.

Build CI/CD pipelines for dbt deployments using Git-based workflows.

Troubleshoot production issues and perform root cause analysis.

Ensure compliance with security, governance, and data privacy standards.

Participate in Agile ceremonies including sprint planning, code reviews, and release activities., * Strong hands-on experience with Databricks

• PySpark
• Spark SQL
• Delta Lake
• Delta Live Tables
• Unity Catalog
• Auto Loader
• Spark Optimization
• Job Clusters
• Workflow Scheduling
• Performance Tuning

dbt

• Advanced dbt Core
• dbt Cloud
• Incremental Models
• Snapshots
• Macros
• Seeds
• Tests
• Documentation
• Packages
• Source Freshness
• Exposures

Programming

• Advanced SQL
• Python
• PySpark
• Spark SQL
• Shell Scripting

Data Engineering

• Data Warehousing
• Data Modeling
• ELT
• ETL
• CDC
• Slowly Changing Dimensions (SCD)
• Data Lake
• Lakehouse Architecture
• Metadata Management
• Data Lineage

Cloud Platforms

• AWS / Azure / Google Cloud Platform
• Object Storage (S3, ADLS, GCS)

Orchestration

• Apache Airflow
• Azure Data Factory
• Databricks Workflows

DevOps

• Git
• Azure DevOps
• GitHub Actions
• Jenkins
• CI/CD
• Terraform (Preferred)

Snowflake

• 5+ years of hands-on Snowflake experience
• Snowflake SQL
• Data Sharing
• Streams & Tasks
• Time Travel
• Zero Copy Cloning
• Snowpipe
• Secure Views
• RBAC
• Query Optimization
• Performance Tuning
• Warehouse Management
• Cost Optimization