Job Title: Data Office Developer (SQL, Python, ETL, Data Warehousing)
Role: Data Office Developer
Key Responsibilities
• Design, develop, and maintain database objects, scripts, queries, and data processing logic using SQL and Python
• Analyze business and technical requirements and translate them into scalable data solutions
• Support data extraction, transformation, loading, validation, reconciliation, and reporting activities across multiple data platforms
• Develop and optimize SQL queries, stored procedures, and scripts to support data analysis, reporting, and operational needs
• Work with relational and cloud-based databases such as Oracle, IQ, BigQuery, and HANA, as applicable
• Collaborate with business analysts, data analysts, architects, quality engineering teams, and business stakeholders to understand data requirements and resolve issues
• Assist in data modeling activities, including understanding source-to-target mapping, relationships, business rules, and data lineage
• Support dashboard/reporting development or validation using tools such as Tableau and Looker
• Perform data quality checks, troubleshoot data issues, and support root cause analysis for defects or production incidents
• Prepare and maintain technical documentation, data mapping documents, design notes, deployment steps, and support handover materials
Must Have Skills
• Strong hands-on experience with SQL, including writing, debugging, and optimizing complex queries
• Proficiency in Python for data processing, automation, scripting, and analysis
• Solid understanding of database concepts, including tables, views, joins, indexes, keys, normalization, stored procedures, and data integrity
• Ability to analyze data, troubleshoot issues, and validate results across source and target systems
• Experience working with large datasets and applying data quality, reconciliation, and validation techniques
• Strong communication skills with the ability to work with technical and business stakeholders
Good to Have Skills
• Experience with database platforms such as Oracle, IQ, BigQuery, and SAP HANA
• Understanding of ETL concepts, including extraction, transformation, loading, scheduling, monitoring, and error handling
• Knowledge of data modeling concepts such as conceptual, logical, and physical models, star schema, snowflake schema, facts, dimensions, and source-to-target mapping
• Experience with reporting and visualization platforms such as Tableau and Looker
• Exposure to data warehousing, analytics platforms, cloud data services, and enterprise reporting environments