Senior Data Engineer

Nortal is a remote-first, global software consultancy specializing in modern custom software development. We employ CI/CD processes across agile, distributed teams delivering highly-performant, scalable, cloud-native applications for Fortune 100 customers. The US headquarters is in Kirkland, WA. We have over 1100 employees world-wide.  

Are you a forward-thinking Data Engineer? Join our expanding team of analytics experts. We're seeking a Senior Data Engineer to enhance and optimize our data and pipeline architecture, enrich data flow and collection for cross-functional teams. Our ideal candidate is an adept data pipeline builder and wrangler, adept at constructing data systems from the ground up. As a Data Engineer, you'll collaborate with software developers, database architects, data analysts, and data scientists on various data initiatives, ensuring consistent and optimal data delivery architecture across ongoing projects. If you're self-directed and thrive in catering to diverse teams, systems, and products, and if you're excited by the chance to revamp our reference data architecture for our next-gen products and data strategies, we want to hear from you. 

• Designing and implementing data and application integrations, as well as data pipelines on both existing and new information systems. 
• Constructing secure data pipelines, with a focus on automation through CI/CD techniques. 
• Identifying and resolving data quality issues in collaboration with the data team. 
• Preparing data for business users, data analysts, and data scientists. 
• Communicating directly with clients and product owners. 
• Supporting system design. 
• Assisting with issue triage, diagnosis, and resolution. 
• Collaborating on code reviews and solutions with other developers. 
• Contributing to system development methodologies and staying informed about evolving technologies, techniques, architectures, and hardware relevant to data management and platforms. 
• Playing a pivotal role in the introduction of new technologies and tools. 
• Ensuring robust data security through encryption, access controls, and authentication mechanisms to maintain data integrity and confidentiality across its lifecycle.  

• 3-5 years of Data Engineering experience. 
• Extensive Python and PySpark experience. 
• Strong experience with the Azure, Microsoft Fabric is a significant advantage. 
• Experience constructing and automating effective data pipelines. 
• Infrastructure-as-code implementation (e.g., Liquibase, Flyway). 
• Hands-on experience with various data types (structured, semi-structured, unstructured, JSON, AVRO, ORC, Parquet, Iceberg, Arrow). 
• Proficiency in source code control using Git. 
• Proficiency in mainstream databases (e.g., SQL Server, Oracle, MySQL, DB2).
• Data Modeling expertise.  
• Understanding of diverse Data & Analytics hybrid architectures, including Data Lake, Data Warehouse, Data Mesh, Enterprise Data Hub, Data Fabric, and Delta Lake with real-time, batch, and micro-batch workloads.
• Expertise in API programming interfaces such as JDBC, ODBC, REST API, and SOAP API. 
• Expertise in Data Warehousing and Cloud Platforms (e.g., Snowflake, Redshift, Azure Synapse). 
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