Senior Data Engineer

Ascendion is looking for a Senior Data Engineer (Snowflake) who will be responsible for designing, building, and maintaining scalable data pipelines and dimensional data models across Bronze, Silver, and Gold zones of a modern data lakehouse. The role will support enterprise reporting and analytics while driving engineering best practices, solution design, and technical mentorship within the team. Qualifications: 5+ years of experience in Data Engineering , with strong experience in designing and developing enterprise data solutions. Strong hands-on experience with Snowflake and Python for data engineering, automation, and pipeline development. Understanding and practical experience with Medallion Architecture , including Bronze, Silver, and Gold data zones . Strong knowledge of dimensional modeling , including fact and dimension tables, star/snowflake schemas, and data warehouse design principles. Hands-on experience implementing Slowly Changing Dimensions (SCD), particularly SCD Type 2 . Strong understanding of Snowflake architecture, including micro-partitions, query optimization, clustering, and performance tuning . Experience with Snowflake Streams and incremental/CDC-based data processing. Knowledge of Apache Iceberg and modern lakehouse architecture is highly preferred. Strong understanding of data engineering fundamentals, data pipeline architecture, ETL/ELT patterns, and data quality. Ability to participate in technical discovery, solution design, and architecture discussions . Strong analytical and problem-solving skills with the ability to troubleshoot complex data engineering issues. Experience working in Agile environments and collaborating with cross-functional technical and business teams. Strong communication skills and the ability to mentor and provide technical guidance to other engineers. Job Description: Design, develop, and maintain scalable data pipelines using Python and Snowflake across Bronze, Silver, and Gold layers of a Medallion Architecture . Develop and maintain dimensional data models to support enterprise reporting, analytics, and downstream data consumption. Implement Slowly Changing Dimensions (SCD Type 2) and other data transformation strategies to maintain historical data accurately. Design efficient Snowflake solutions considering micro-partitioning, clustering, query performance, and data storage optimization . Build and manage Snowflake data ingestion and transformation workflows, including the use of Streams and other native Snowflake capabilities for incremental data processing. Contribute to data lakehouse architecture and evaluate technologies and patterns such as Apache Iceberg where applicable. Participate in discovery and solution design discussions , translating business and technical requirements into scalable data engineering solutions. Apply data engineering best practices around data quality, performance, scalability, reliability, and maintainability . Troubleshoot data pipeline and platform issues, identify root causes, and implement sustainable solutions. Collaborate with architects, analysts, developers, and business stakeholders to deliver reliable data solutions for enterprise reporting and analytics. Provide technical guidance, conduct code/design reviews, and mentor junior and mid-level data engineers . Help establish and continuously improve engineering standards, development practices, and architectural patterns. Why Ascendion? At Ascendion , you'll work on enterprise-scale technology initiatives where data engineering plays a critical role in business transformation. You'll have the opportunity to work with modern data platforms such as Snowflake, contribute to scalable lakehouse architectures, solve complex engineering challenges, and grow as a technical leader while collaborating with experienced engineering and architecture teams. Ascendion Highlights Work on enterprise-scale data and analytics projects Gain exposure to modern cloud and lakehouse technologies Design and implement scalable data architectures and pipelines Collaborate with experienced engineering, architecture, and business teams Opportunity for technical leadership and mentoring Drive engineering best practices and contribute to modern data transformation initiatives