Summary/Objective
Emburse 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
- 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
- Required: Bachelor’s degree in Computer Science or related field, or equivalent years’ 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
Skills Required
- 4+ years of data engineering experience related to data acquisition, data pipeline or analytics systems
- Bachelor's degree in Computer Science or related field, or equivalent experience
- Advanced working SQL knowledge
- Experience with relational or columnar databases and data warehouses/data lakes
- Experience with modern data pipeline or data workflow management tools
- Experience with semantic data modeling for AI optimization
- Experience with Python in a full SDLC/production deployment environment
- Ability to develop extraction, transformation, and loading code (Python, Java, .NET, or ETL tools)
- Understanding of testing and integration testing techniques and implementing unit/integration tests
- Ability to read and understand existing code, perform code reviews, and contribute to SDLC/agile processes
- Understanding of OWASP and secure software development practices
- Experience with AWS services
- Experience working with Snowflake
- Experience working with Looker or equivalent BI suite
- Experience with Fivetran or equivalent ETL/ELT suite
- Experience with Databricks or equivalent Spark-based suite
- Financial industry experience
What We Do
Emburse humanizes work by empowering business travelers, finance professionals and CFOs to eliminate manual, time-consuming tasks so they can focus on what matters most. Emburse brings together some of the world’s most powerful and trusted expense and AP automation solutions, including Abacus, Captio, Certify, Chrome River, Nexonia and Tallie. The company’s innovative offerings, which are uniquely tailored for specific industries, company sizes, and geographies, are trusted by more than 4.5 million users in more than 120 countries. Over 14,000 customers, from start-ups to global enterprises, including Boot Barn, Grant Thornton, Telefónica, Lufthansa Systems, and Toyota rely on Emburse to make faster, smarter decisions, empower business travelers to recapture lost nights and weekends spent doing tedious expense management, and help make users’ lives -- and their businesses -- better.
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