This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a Senior Data Engineer to lead the retirement of Talend Open Studio and redesign our data integration architecture using modern ELT principles. This role will evaluate, select, and implement a scalable replacement platform, with strong preference for Snowflake-native solutions (Openflow and dbt), while remaining open to third-party tools such as Fivetran or Matillion. The ideal candidate has hands-on experience modernizing legacy ETL environments, implementing Git-integrated data workflows, and embedding governance, lineage, and data quality controls into enterprise data platforms. Key Responsibilities - Lead the sunset of Talend Open Studio and migrate ETL pipelines to a modern ELT framework. - Design and implement scalable ELT pipelines in Snowflake. - Leverage Snowflake Openflow (Apache NiFi-based) and dbt where appropriate. - Integrate pipelines with Git-based version control and CI/CD practices. - Embed transparent data lineage, data quality monitoring, and semantic modeling. - Optimize Snowflake performance, scalability, and cost efficiency. - Partner with BI stakeholders to simplify downstream reporting and analytics. Qualifications - 5+ years of data engineering experience. - Strong Snowflake expertise (modeling, performance optimization, security). - Hands-on experience with dbt. - Experience with Apache NiFi or similar orchestration tools. - Experience modernizing legacy ETL platforms. - Strong SQL and dimensional data modeling skills. - Experience integrating data workflows with Git. Benefits - All our positions are Remote and are available as Full Time Employment or B2B Contracts.

• Define and own enterprise-wide data architecture and modeling standards. • Design conceptual, logical, and physical data models across our core business domains. • Build our modern data platform – pipelines, lakehouse/warehouse layers, and medallion-architected datasets. • Create scalable, AI-ready data environments that support analytics, data products, and future AI/ML initiatives. • Partner with engineers, analytics teams, and business stakeholders to ensure data is reliable, reusable, and secure. • Implement strong data governance, observability, and cataloging to enable true self-service and support data mesh principles. • Drive strategic technical decisions, influencing platform and tooling choices with a modern, cloud-native mindset. • Translate complex data and AI concepts into simple, compelling narratives for non-technical audiences. • Advise on emerging AI architectures, including RAG patterns and enterprise AI agents. • Shape a healthy, modern, future-proof data environment from the ground up – without technical debt.

• Design, develop, and maintain core Python ETL framework • Develop and optimize automated refresh pipeline with AWS services • Build Python integrations with external systems • Identify and eliminate manual bottlenecks in data onboarding • Ensure data integrity and security throughout project lifecycles

• Complete analysis, design, and development of BI solutions • Database development primarily in SSIS, Databricks, and SQL • Collaborate with other developers to create and implement the best approach solution(s) • Review queries and troubleshoot for performance issues • Assist with the analysis and extraction of relevant information from large amounts of historical business data to feed data science initiatives • Participate and support the design and documentation of processes for large-scale data analyses, model development, model validation, and model implementation • Support and maintain a positive safety culture by following all safety policies and procedures and actively contributing to a safe working environment