Role: Data Office Developer – Job Description
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.
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