> Markdown version of [/jobs/ext/4095992-data-developer-sql-python](https://www.wearedevelopers.com/jobs/ext/4095992-data-developer-sql-python). 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). --- # Data Developer (SQL & Python) - **Company:** Information Tech Consultants - **Location:** Greater London, UK - **Experience:** Experienced - **Salary:** £35,000.0 - £45,000.0 - **Contract:** Permanent contract - **Skills:** Databases, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Systems, Database Development, Database Queries, Python (Programming Language), Standard Sql, SQL Databases, Data Processing, Data Storage Technologies, Snowflake, Information Technology, Data Management, Data Pipelines, Databricks - **Published:** October 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=12be4151dda7d22b ## About the Role * 2-5 years of experience in Data Development or Data Engineering. * Strong SQL skills. * Good knowledge of Python. * Knowledge of Databricks and Snowflake is preffered. * Good understanding of databases and data processing. * Strong analytical and problem-solving skills., * 2-5 years of relevant professional experience * Bachelor's degree in Computer Science, IT, Engineering, or a related field * Applicants should be open to relocation within the UK based on client project requirements. ## Description We are looking for a Data Developer with strong SQL and Python skills and hands-on experience. The role involves developing data solutions, building data pipelines, and working with data platforms., * Develop and maintain data solutions using Python and SQL. * Build and maintain data pipelines using Databricks. * Work with Snowflake for data storage, processing, and querying. * Write and optimize SQL queries. * Develop ETL processes and data workflows. * Experience with ETL/ELT and data pipelines * Integrate data from multiple sources. * Perform data validation and quality checks. * Troubleshoot data and pipeline issues. * Collaborate with developers, analysts, and technical teams. * Maintain technical documentation.