Sr.Data Engineer ( Mid level- Snowflake

3-5 Years

Full-Time

CU Rise Analytics is a Virginia based CUSO with global operations that was started with the sole mission of helping credit unions better understand, serve and support their members in the most effective & efficient manner. CU Rise’s service offering centers around bringing Data Science and forward-looking Data Technologies to our clients. Our core competencies are Data Analytics, Predictive Modelling, Business Intelligence & Technology services.

We are the only ‘Pure-play’ analytics company focused on bringing this expertise to credit unions.

Trellance is a leading provider of business analytics and technology consulting for credit unions, helping them meet the financial needs of today’s digital consumer. With a comprehensive suite of data science solutions, professional staffing and professional services, the Trellance team ensures credit unions increase efficiency, manage risk, and improve member experience. As credit unions’ tech partner, Trellance brings them to the next frontiers of fintech, filled with powerful tools such as artificial intelligence and machine learning.

Data In. Insights out.

We are seeking skilled Data Engineers with expertise in SSIS and SQL to join our team. As a Data Engineer, you will be critical in our client’s work of automation import and export and cloud migration from on-premises systems to a cloud-based data platform. You will be responsible for building robust and efficient SSIS package, transforming raw data, and ensuring smooth data consumption.

Experience with Snowflake is a plus.

• Collaborate with cross-functional teams to understand data requirements and design performant, efficient, and secure data pipelines from the landing zone to the consumption level in SQL server and SSIS.
• Utilize native SSIS capabilities to implement data transformations, aggregations, and enrichments to meet business needs.
• Develop and maintain data ingestion processes from various sources to on-premises sources to the landing zone, ensuring data integrity and accuracy throughout the pipeline.
• Work closely with the architecture team to ensure seamless integration of data sources.
• Optimize SSIS Package performance, scalability, and reliability, implementing best practices and monitoring mechanisms.
• Collaborate with data analysts and other stakeholders to understand data consumption requirements and provide solutions for efficient data retrieval.
• Ensure compliance with data governance policies and industry standards throughout the data engineering process.
• Continuously stay updated with the latest advancements in Snowflake and data engineering techniques, sharing knowledge and insights with the team.

• Bachelor’s degree in computer science, Engineering, or a related field (or equivalent practical experience).
• Proven experience as a Data Engineer with a focus on SQL Server, including hands‑on experience in building end-to-end data pipelines.
• Strong understanding of SQL Server architecture, data warehousing concepts, and ETL/ELT methodologies.
• Expert knowledge of SQL (T‑SQL specifically for SQL Server), including writing complex queries, stored procedures, and performance optimization techniques.
• Hands‑on experience with Microsoft SQL Server Integration Services (SSIS) is essential, along with general knowledge of other ETL tools.
• Familiarity with cloud platforms (e.g., AWS, Azure) and their data services.
• Solid understanding of data modeling principles and ability to design efficient data structures within Snowflake.
• Strong problem‑solving skills and ability to analyze complex data requirements to develop effective solutions.
• Excellent communication and collaboration skills, with the ability to work effectively in cross‑functional teams.
• Proactive and self‑motivated with a passion for data engineering and delivering high‑quality solutions.

• Snowflake certification(s) in Data Engineering or related areas.
• Strong understanding of Snowflake architecture.
• Experience integrating external systems and services with Snowflake.
• Proficiency in SQL for data manipulation and transformation within Snowflake.
• Expertise and experience using Snowflake procedures, functions, streams, tasks, external stages, and external tables.
• Expertise and experience using Snowpipe.
• Experience with Snowpark, especially with Python.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Knowledge of Python or other scripting languages for data processing and automation.
• Expertise in Banking Data/Domain.
• Familiarity with data governance frameworks and practices.
• Experience with data visualization tools (e.g., Tableau, Power BI) for reporting and analytics.