• Architect and develop scalable data pipelines and models using Snowflake and dbt • Design and operate orchestration using Airflow, Dagster, Prefect, or similar • Define modeling standards, storage patterns, and performance strategies • Collaborate on backend APIs, services, integration layers, and limited frontend interfaces supporting data-driven features • Contribute to CI/CD, environment management, and automated pipeline delivery • Implement quality checks, lineage, SLAs, and observability • Mentor engineers and drive architectural best practices • Participate in system design and multi-team architectural planning

• Translate SAP table structures and business processes (SD, MM, FI, O2C, P2P) into scalable data models • Design and develop robust ETL/ELT pipelines to replicate data from SAP S/4HANA, ECC, and other sources into BigQuery • Implement data warehousing best practices and advanced SQL transformations (Stored Procedures, Table Functions, Window Functions) • Develop and manage Slowly Changing Dimensions (SCD), Change Data Capture (CDC), and entity resolution strategies • Optimize queries using partitioning, clustering, and performance tuning techniques • Manage data replication tools and pipeline orchestration processes • Ensure data quality, governance, consistency, and scalability across systems

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.