Developer

<div></div><p><strong>Job Summary</strong></p><p>This hybrid Sr Developer role focuses on designing and delivering robust data warehousing and integration solutions using SQL and TALEND ETL for an international organization. The role requires eight to ten years of experience in modern data practices translating complex business needs into scalable data pipelines that improve analytics reporting and decision making while ensuring reliability performance and long term maintainability across diverse enterprise systems.</p><br><p><strong>Responsibilities</strong></p><p>Talend & MSQL SSIS Data Integration</p><p>AWS RDS</p><p>MS SQL Server 2018 and later</p><p>PostgreSQL</p><p>S3 file storage</p><p>DynamoDB</p><p>TFS</p><p>GIT</p><li>Design and implement scalable data warehousing solutions that consolidate diverse enterprise data into well structured models to enable accurate analytics and reporting across the organization.</li><li>Develop and optimize complex SQL queries and stored procedures to support high performance data retrieval transformation and loading activities that directly serve business critical applications and dashboards.</li><li>Build robust data integration workflows using TALEND ETL to orchestrate ingestion transformation and delivery processes that maintain data quality and consistency across multiple source and target platforms.</li><li>Analyze existing data pipelines and warehouse structures to identify performance bottlenecks and then apply tuning strategies that improve throughput reliability and resource utilization for day to day operations.</li><li>Collaborate closely with business and analytics stakeholders to translate data requirements into technical specifications and deliver solutions that provide trusted information for strategic and operational decisions.</li><li>Create detailed technical documentation for data models mappings ETL jobs and operational procedures so that support teams and future developers can maintain and extend solutions with confidence.</li><li>Implement rigorous data validation reconciliation and error handling mechanisms within ETL workflows to minimize data defects and ensure that downstream consumers receive complete and accurate information.</li><li>Monitor daily data loads and batch processes in the hybrid work environment and proactively troubleshoot issues to minimize disruption to reporting cycles and dependent applications.</li><li>Coordinate with infrastructure and database teams to plan capacity indexing partitioning and configuration changes that keep data warehouse environments secure performant and resilient.</li><li>Apply industry standard coding practices version control and peer review processes to TALEND ETL jobs and SQL scripts to maintain code quality traceability and long term sustainability.</li><li>Contribute to continuous improvement by evaluating new data integration approaches patterns and tools that can enhance efficiency maintainability and business value in hybrid work scenarios.</li><li>Support incident and problem management by performing root cause analysis on data issues and propose targeted remediation steps that prevent recurrence and improve trust in enterprise data.</li><li>Advise project managers and product owners on realistic effort estimates technical risks and dependencies related to data warehousing and integration so that delivery timelines and expectations remain aligned.</li><br><p><strong>Qualifications</strong></p><li>Bring deep practical experience in enterprise data warehousing concepts including dimensional modeling slowly changing dimensions and data lifecycle management from at least eight years of focused work.</li><li>Demonstrate advanced proficiency in SQL across major relational database platforms with strong capability in query tuning indexing and complex joins for large volume datasets.</li><li>Show extensive hands on expertise in TALEND ETL including job design component selection error handling and deployment practices that support robust production data pipelines.</li><li>Exhibit strong knowledge of data integration patterns such as batch streaming and near real time processing and understand when each pattern is appropriate for business scenarios.</li><li>Apply sound understanding of data quality principles including validation standardization deduplication and reconciliation to maintain trusted data across the warehouse ecosystem.</li><li>Utilize experience working in hybrid models that combine remote and office collaboration demonstrating effective communication and documentation to keep distributed teams aligned.</li><li>Use familiarity with analytics and reporting tools at a conceptual level to design data structures and integration flows that meet the needs of business intelligence and data science stakeholders.</li>