Sr. Data Engineer at Oportun in San Carlos, CA
Department Overview ABOUT TECHNOLOGY @ OPORTUN Artificial Intelligence and a digital platform are essential to our ability to fulfill Oportun's financially inclusive mission. The Technology team @ Oportun is dedicated to this mission which we enable by creating, delivering, and maintaining elegant, intuitive, and performant systems to support the needs of our customers and business partners. Overview Oportun is looking for a Senior Software Engineer (Data Platform) to join our Data Engineering team. In this role you will play key part in developing our next generation Data Platform to support all our operation processes, data sciences and business intelligent data processing. Our team works with:
Big Data ecosystem Relational data modeling and batch processing on SQL databases Distributed processing framework like Spark Streaming data platforms like Kafka or AWS Kinesis Realtime stream processing frameworks like Flink, Spark Streaming or Kafka Stream Cloud computing systems like Amazon Web Services Big Data analytics tools like Hive or Spark SQL If you have a passion for writing data processing software, including acquisition, cleansing, correlation, organization, analysis and machine learning, and the challenge of building a new data infrastructure from the ground up excites you, we would love to hear from you. Responsibilities Design, develop and maintain Java/Python based Data Platforms including Data Lake, Operational Datamart and Analytics Data Warehouses Design and build scalable Java/Python based ELT/ETL workflows to transform and integrate data into Data Platform/Data Lake Develop data strategy and roadmap for data technologies Play multiple roles that span data architecture, design, data warehousing, and ELT/ETL processes Work closely with product management, business, engineers, cross-functional analysts, and data scientist Demonstrates master hands-on capability to drive components to delivery from inception to final product. Recommends and contributes to software engineering best practices, including those that have enterprise-wide impact. Takes accountability for the quality, total cost of ownership, maintainability and security of any component or application produced. Performs as an expert in all parts of the software development lifecycle (e.g., coding, testing, development) and coaches other around such practices. Converses in many technologies and learns new technologies quickly. Ability to provide a clear and concise explanation of business strategy, technical concepts, designs or implementation to a non-technical audience. Stays abreast of industry trends and technologies and knows when/how/if to apply them appropriately. Qualifications Master's in Computer Science 5
years of experience working as a software developer in Data Engineering, Data Warehousing/BI team 5
years of experience in Java/Python development 3
years of experience in SQL and Relational Databases Experience using AWS to build end to end distributed technical solutions (ALB, ECS, EC2, Fargate, Lambda,etc.) and as well as general cloud native applications. Familiarity with messaging frameworks (RabbitMQ, Kafka, Kinesis) as well as relational (MySQL/Postgres) and non-relational (Mongo, Cassandra, ElasticSearch) databases is a plus. Experience with Git and VCS, TDD and BDD frameworks for Python and Javascript. Extensive experience working with structured and unstructured data platforms, ELT/ETL, and Data Modeling Experience with Test Driven Development JUnit or TestNG frameworks Knowledge and experience with big data systems such as Spark is a plus Experience with Machine Learning and Statistical Frameworks is a plus Experience with NoSQL Database like MongoDB is a plus
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine Learning, Database Administration, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
Big Data ecosystem Relational data modeling and batch processing on SQL databases Distributed processing framework like Spark Streaming data platforms like Kafka or AWS Kinesis Realtime stream processing frameworks like Flink, Spark Streaming or Kafka Stream Cloud computing systems like Amazon Web Services Big Data analytics tools like Hive or Spark SQL If you have a passion for writing data processing software, including acquisition, cleansing, correlation, organization, analysis and machine learning, and the challenge of building a new data infrastructure from the ground up excites you, we would love to hear from you. Responsibilities Design, develop and maintain Java/Python based Data Platforms including Data Lake, Operational Datamart and Analytics Data Warehouses Design and build scalable Java/Python based ELT/ETL workflows to transform and integrate data into Data Platform/Data Lake Develop data strategy and roadmap for data technologies Play multiple roles that span data architecture, design, data warehousing, and ELT/ETL processes Work closely with product management, business, engineers, cross-functional analysts, and data scientist Demonstrates master hands-on capability to drive components to delivery from inception to final product. Recommends and contributes to software engineering best practices, including those that have enterprise-wide impact. Takes accountability for the quality, total cost of ownership, maintainability and security of any component or application produced. Performs as an expert in all parts of the software development lifecycle (e.g., coding, testing, development) and coaches other around such practices. Converses in many technologies and learns new technologies quickly. Ability to provide a clear and concise explanation of business strategy, technical concepts, designs or implementation to a non-technical audience. Stays abreast of industry trends and technologies and knows when/how/if to apply them appropriately. Qualifications Master's in Computer Science 5
years of experience working as a software developer in Data Engineering, Data Warehousing/BI team 5
years of experience in Java/Python development 3
years of experience in SQL and Relational Databases Experience using AWS to build end to end distributed technical solutions (ALB, ECS, EC2, Fargate, Lambda,etc.) and as well as general cloud native applications. Familiarity with messaging frameworks (RabbitMQ, Kafka, Kinesis) as well as relational (MySQL/Postgres) and non-relational (Mongo, Cassandra, ElasticSearch) databases is a plus. Experience with Git and VCS, TDD and BDD frameworks for Python and Javascript. Extensive experience working with structured and unstructured data platforms, ELT/ETL, and Data Modeling Experience with Test Driven Development JUnit or TestNG frameworks Knowledge and experience with big data systems such as Spark is a plus Experience with Machine Learning and Statistical Frameworks is a plus Experience with NoSQL Database like MongoDB is a plus
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine Learning, Database Administration, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
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