• Develop, and maintain database solutions and data warehouse architectures using MSSQL 2019/2022 and MySQL 8. • Collaborate with stakeholders to gather requirements and understand business needs for data storage and processing. • Develop and maintain ETL processes using SSIS, BIML, and DBT to ensure efficient data integration and transformation. • Implement and manage solutions within Power BI Fabric for enterprise-scale data analytics. • Write complex SQL queries, stored procedures, functions, and triggers to support application and reporting requirements. • Optimize query performance through indexing strategies, execution plan analysis, and database tuning techniques. • Troubleshoot and resolve database performance issues, data integrity problems, and system bottlenecks. • Monitor database health, perform capacity planning, and implement proactive maintenance strategies. • Develop automation scripts using PowerShell and Python to streamline database operations and maintenance tasks. • Ensure data security, backup and recovery procedures, and compliance with organizational standards. • Utilize version control tools such as Git and project management tools like Jira and Confluence or similar platforms as required. • Work effectively in a team environment, collaborating on concurrent developments and contributing to team success. • Document database architectures, ETL processes, standards, and procedures. • Stay current with database technologies, best practices, and emerging trends in data warehousing. • Provide technical guidance and support to team members and end-users as needed. • Contribute to continuous improvement initiatives related to data management and analytics infrastructure.

• Lead data analysis, mapping, and transformation efforts • Collaborate with project teams to define requirements • Perform comprehensive data analysis and cleansing • Develop, test, and implement SQL-based ETL scripts • Validate migration outcomes through rigorous testing

• Build and maintain production-ready data pipelines using DBT, Snowflake, and modern orchestration tools. • Own data engineering features end-to-end, from implementation through optimization and deployment. • Fix and improve existing pipelines - identify bottlenecks, resolve issues, and enhance performance. • Drive automation initiatives across the data stack to accelerate delivery and reduce manual interventions. • Provide 2nd line support for B2B customers - investigate data issues, clarify edge cases, and ensure customers can trust their data. • Design and implement new data import pipelines as we expand our data source coverage. • Implement data quality improvements - validation, monitoring, and testing to ensure reliable, accurate data delivery. • Contribute to code reviews, architectural discussions, and data engineering best practices.

• Collaborate with team members and stakeholders to understand data requirements and contribute to building scalable data pipelines and workflows in Databricks. • Develop and implement ETL/ELT processes using Databricks, Python, SQL, and related tools to ingest, transform, and prepare data. • Assist in optimizing data workflows for better performance, reliability, and cost-efficiency within Databricks environments. • Support the creation and maintenance of data models, tables, and integrations in cloud platforms (Azure, AWS, or similar). • Work closely with cross-functional teams (data analysts, scientists, and engineers) to deliver clean, accessible data for analytics and reporting. • Monitor data pipelines, troubleshoot basic issues, and contribute to documentation and best practices. • Stay curious about new Databricks features and data engineering trends to support ongoing improvements.