Create and manage scalable data integration workflows to move information from diverse sources into Snowflake.
Build and refine data warehouse components such as databases, tables, views, and schemas within Snowflake.
Apply SQL, dbt, Python, or comparable tools to execute data transformations in Snowflake-based environments.
Optimize virtual warehouse configurations for speed, resource usage, and cost-effectiveness.
Leverage Snowflake capabilities like stages, tasks, streams, time travel, cloning, and data sharing as needed.
Handle ingestion and processing of both structured and semi-structured formats including JSON, Avro, and Parquet.
Track and improve query performance, resolve execution issues, and tune workloads for stability and scale.
Enforce data accuracy through validation rules, quality checks, and monitoring systems.
Collaborate with analysts, BI teams, architects, and business partners to convert requirements into technical implementations.
Follow data governance, security protocols, access controls, and compliance standards within the Snowflake platform.
Support automated deployment pipelines, CI/CD practices, and infrastructure as code for data workflows.
Document technical designs, pipeline logic, data models, and operational procedures.

Competitive market rate

Hybrid

Collaborative engineering team focused on data platforms and analytics solutions

Design, build, and maintain scalable ETL/ELT pipelines to ingest data from multiple source systems into Snowflake.
Develop and optimize Snowflake data warehouse structures, including databases, schemas, tables, views, and materialized views.
Implement data transformation logic using SQL, dbt, Python, or similar tools within Snowflake-centric architectures.
Manage and optimize Snowflake virtual warehouses for performance, concurrency, and cost efficiency.
Use Snowflake features such as stages, tasks, streams, time travel, zero-copy cloning, and secure data sharing where appropriate.
Load and process structured and semi-structured data, including JSON, Avro, and Parquet.
Monitor query performance, troubleshoot failures, and tune Snowflake workloads for reliability and scalability.
Implement data quality checks, validation frameworks, and monitoring for production pipelines.
Work closely with analysts, BI developers, architects, and business stakeholders to translate data requirements into technical solutions.
Apply best practices for data governance, security, role-based access control, and compliance within Snowflake.
Support CI/CD, automation, and deployment processes for data engineering workflows.
Maintain technical documentation for pipelines, models, Snowflake objects, and operational proc

Available

Endava is hiring a Senior Data Engineer (Snowflake)