Database Developer

Roles & Responsibilities

Job Summary

We are seeking an experienced Senior Developer to design and optimize data solutions using PL/SQL, SQL,ETL, and Microsoft SSIS, supporting enterprise data warehousing initiatives in a hybrid work model. This role

centers on building robust scheduling workflows and integrating multi-channel and supply chain data to improve operational insights and drive informed business decision-making for global stakeholders.

Key Responsibilities

• Design and develop complex PL/SQL and SQL procedures, functions, and queries that ensure accurate,

performant, and reliable data processing for enterprise reporting needs.

• Implement and optimize ETL workflows using Microsoft SSIS to move, transform, and validate large

datasets from diverse operational systems into centralized warehouse structures.

• Configure and manage scheduling for batch jobs and data pipelines to guarantee timely data availability

aligned with business-day operations and service level expectations.

• Analyze existing data warehousing concepts and models to propose improvements that enhance

scalability, maintainability, and analytical value across multiple business units.

• Collaborate with cross-functional teams to translate multi-channel and supply chain management data

requirements into well-structured technical solutions supporting strategic initiatives.

• Perform detailed root cause analysis and remediation of data quality issues to ensure downstream

analytics, dashboards, and operational decisions are based on trustworthy information.

• Document technical designs, mappings, data flows, and deployment steps in clear, reusable formats to

support ongoing maintenance, future enhancements, and audit readiness.

• Conduct unit, integration, and regression testing of PL/SQL, SQL, and ETL components to verify

functional accuracy, performance benchmarks, and alignment with enterprise standards.

• Provide production support for data warehouse jobs and SSIS packages by monitoring execution,

troubleshooting failures, and implementing preventive improvements to reduce recurrence.

• Engage with stakeholders in a hybrid work setting to gather requirements, demonstrate solutions, and

refine deliverables to consistently meet business expectations.

• Contribute to continuous improvement of data engineering practices by proposing new patterns, tools,

and methods that increase automation, reliability, and transparency of data flows.

• Align daily development activities with organizational goals, ensuring data solutions enable better

customer experiences, optimized supply chains, and informed decision-making across markets.

• Ensure compliance with internal quality guidelines and external regulatory expectations by

implementing robust controls, validations, and traceability within data warehouse ecosystems.