> Markdown version of [/jobs/ext/1294571-snowflake-expert-developer](https://www.wearedevelopers.com/jobs/ext/1294571-snowflake-expert-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Snowflake Expert Developer - **Company:** adesso SE - **Location:** Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Amazon S3, ARM Architecture, Cloud Database, Cloud Storage, Data Validation, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Structures, Data Systems, Python (Programming Language), OpenFlow, DataOps, Simple Data Format, Software Deployment, SQL Databases, Data Streaming, Unstructured Data, Data Processing, Azure Data Factory, Snowflake, Change Data Capture, Collibra, Low Latency, AWS Glue, Real Time Data, Apache Kafka, Data Pipelines - **Published:** July 16, 2026 - **Apply:** https://jobs.adesso-group.com/talentcommunity/apply/1360634655/?locale=en_GB ## About the Role Experience: 10+ years of Snowflake development experience, * 10+ years of hands-on experience in Snowflake development. * Working knowledge of Snowflake Openflow, Snowflake CoCo, and Cortex Cost Management. * Strong expertise in CDC (Change Data Capture) and incremental data processing techniques. * Experience working with batch, micro-batch, and real-time ingestion patterns. * A builder's mindset with the ability to own data pipelines end-to-end, from architecture and development through production deployment and monitoring. ## Description We are seeking a highly experienced Snowflake Expert Developer to lead the design, development, optimization, and management of end-to-end data pipelines on the Snowflake platform. The ideal candidate will have deep expertise in modern data engineering practices and a strong track record of delivering scalable, secure, and high-performance data solutions. In this role, you will be responsible for building and maintaining data pipelines from ingestion through transformation to consumption, working across batch, micro-batch, and real-time processing patterns. You will leverage the full Snowflake ecosystem to enable efficient, reliable, and governed data operations that support enterprise analytics and business initiatives. The successful candidate will bring hands-on experience across the Snowflake data engineering stack, a strong understanding of cloud-based data architectures, and the ability to drive solutions from design through production support and optimization., * Set up and manage automated, near real-time data ingestion using Snowpipe and low-latency, event-based streaming ingestion using Snowpipe Streaming. * Configure Internal and External Stages to ingest data from Amazon S3, Azure Blob Storage, and Google Cloud Storage (GCS), including appropriate file formats and External Tables for semi-structured and unstructured data. * Implement Streams for Change Data Capture (CDC) covering inserts, updates, and deletes, and orchestrate pipelines using Tasks and DAG-based Task Graphs. * Build SQL-based ELT transformations and Dynamic Tables for continuous transformation pipelines, and extend transformations using Snowpark (Python, Java, or Scala) where required. * Manage Virtual Warehouses and the broader storage layer, including tables, schemas, and centralized data structures. * Integrate native connectors such as Kafka and Kinesis, and work with external ETL/ELT tools including Azure Data Factory (ADF), Airbyte, and AWS Glue. * Leverage Snowflake Openflow for enterprise-scale data integration and CDC use cases. * Build data validation, monitoring, and pipeline observability capabilities from the outset. * Apply strong governance, security, and access control best practices across all pipelines, and integrate with Collibra where applicable. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Flex your Energy: Building a Cloud-Native Platform for Renewable Energy Communities](https://www.wearedevelopers.com/videos/1990-flex-your-energy-building-a-cloud-native-platform-for-renewable-energy-communities) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Dev Digest 162: AI careers, MCP, AWS best practices & floppy sweaters](https://www.wearedevelopers.com/magazine/571-dev-digest-162-ai-careers-mcp-aws-best-practices-floppy-sweaters) - [What’s the Difference between a Junior, Mid, and Senior Developer?](https://www.wearedevelopers.com/magazine/238-what-s-the-difference-between-a-junior-mid-and-senior-developer)