- 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
- 5+ years of experience in data engineering, analytics engineering, or a similar role.
- Hands-on experience with Snowflake in production environments.
- Advanced SQL skills, including complex query development and query optimization.
- Experience with Snowflake architecture and core objects such as virtual warehouses, databases, schemas, tables (including Iceberg tables), stages, tasks, streams, and views.
- Experience designing and building ETL/ELT pipelines for cloud data platforms.
- Proficiency in Python, Scala, or Java for data processing and automation.
- Experience with data transformation and orchestration tools such as dbt, Airflow, Matillion, Fivetran, or Informatica.
- Knowledge of cloud platforms such as AWS, Azure, or GCP and interoperability capabilities.
- Experience with data modeling, data warehousing concepts, and dimensional modeling.
- Understanding of Snowflake security, access control, and governance best practices.
- Experience with dbt or similar tols and modern ELT patterns in Snowflake.
- Knowledge of Snowflake performance tuning, workload management, and cost optimization strategies.
- Experience integrating Snowflake with cloud storage services such as Amazon S3, Azure Data Lake, or Google Cloud Storage.
- Familiarity with real-time or near-real-time data ingestion patterns.
- Experience with data lineage, metadata management, and governance tools.
- Snowflake certification.
At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.