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. """