Data Engineer

Bottomline is looking for a Data Engineer to design, develop, and maintain the infrastructure and systems required for data storage, processing, and analysis. The Data Engineer will work on implementing data flows to make data available in the Enterprise Data Warehouse and collaborate with data scientists and analysts to optimize models and algorithms.

Requirements

• Bachelor's degree in computer science, data science, software engineering, information systems, or related quantitative field
• At least four (4) years of work experience in data management disciplines
• Proven project experience developing and maintaining data warehouses
• Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI
• Strong ability in programming languages such as Java or Python and other scripting languages
• Previous experience with languages/tools such as SQL
• Significant experience working in the ETL process and building pipeline for data retrieval using Rest API's
• Proficiency in OLAP, Star, Dimensional, and Snowflake schemas
• Basic knowledge of BI Tools – Power BI, Tableau
• Basic knowledge of DevOps tools – GitHub, Atlassian Tools, VS Code etc
• Experience working in a structured development environment
• Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure) and modern data warehouse tools (Snowflake, Databricks)
• Experience with database technologies such as SQL, NoSQL, Oracle, or Teradata
• Experience with using AI in Data Engineering/ Data Analysis work and experience in Data QA
• Knowledge in Apache technologies such as Kafka, Airflow to build scalable and efficient data pipelines (nice to have)
• Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products
• Expert problem-solving skills, including debugging skills
• Excellent business acumen and interpersonal skills
• Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options