Data Engineer III

About this role

Who We Are:   At Emburse, you’ll not just imagine the future – you’ll build it. As a leader in expense intelligence, we are creating a future where technology drives business value and inspires extraordinary results. Our AI-powered platform helps organizations modernize financial operations, increase visibility, and optimize spend across the enterprise. Summary/ObjectiveEmburse data engineers develop the data pipelines and systems in the central platform empowering Emburse’s SaaS products. As a data engineer, you will build the pipelines that populate the data warehouse and data lakes, implement tenant data security, support the data science platforms and techniques, and integrate AI data solutions and APIs with Emburse products and analytics.  The role is based within the Emburse Platform analytics team, a fast moving and product-focused team responsible for delivering next generation business intelligence and data science capabilities across the business.  Emburse, known for its innovation and award-winning technologies employ modern technologies including Snowflake, Data Bricks/Spark, AWS and Looker. In this role you will have access to the best and brightest minds in our industry to grow your experience and career within Emburse.   Essential Functions Technical 4+ years of data engineering experience related to data acquisition, data pipeline or analytics systems Self-sufficient in at least one large area of the data acquisition, data pipeline, analytics codebase, semantic views and an understanding of how a handful of key sub-systems interoperate  Develops code (e.g. python, Java or .net, or with specialized ETL tools) for the extraction, transformation, and loading of data from a variety of data sources Builds analytical tools to utilize, model and visualize data  Can interpret ad-hoc requests for data and translate these into the applicable data operations Develops scripts to automate manual processes, address data quality, enable integration or monitor processes Understands relational databases, columnar databases, development frameworks, and commonly used industry libraries. Understands testing and integration testing techniques Ability to read and understand existing code and offer recommendations for improvement Understanding of OWASP   Process SDLC processes are followed, including adopting agile-based processes/meetings, peer code-reviews, and technical preparations required for scheduled releases. Understands product roadmap and how one contributes to the overall objectives Capable at prioritizing tasks Estimates their own work Learns and applies secure software development practices, reviews code for vulnerabilities and raises awareness of secure programming practices   Impact Optimizes processes, fixes bugs of moderate complexity and demonstrates proficient debugging skills Reviews code for team members, providing in-depth comments Develops new features or enhancements with minimal supervision Delivers medium level refactoring  Implements unit testing and integration testing where needed Produces quality technical documentation Makes technical documentation/knowledge base contributions and technical team presentations   Communication Gives constructive feedback to team members Understanding of industry jargon and business concepts Raises roadblocks and updates estimations as needed   Education: Required: Bachelor’s degree in Computer Science or related field, or equivalent years’ experience   Experience: Advanced working SQL knowledge and moderate experience working with relational or columnar databases  Experience working with a modern scalable data lake or data warehouses Experience working with a modern data pipeline or data workflow management tool Experience working with semantic data modeling for AI optimization Experience working in a product-oriented environment alongside software engineers and product managers Experience with Python in a full SDLC/production deployment environment Preferred: Experience with AWS services, Experience working with Snowflake, Experience working with Looker or an equivalent Business Intelligence suite, Experience working with Fivetran or an equivalent ETL/ELT suite, Experience with Databricks or an equivalent Spark-based suite, Financial Industry experience preferred