We are currently looking for an exceptionally talented Full-Stack Data Engineer to join our 6-person team. The foundation of any cutting edge AI is a comprehensive, high-quality and unique dataset. You will be responsible for building the world’s largest repository of customer service data, which powers all aspects of the Rustle solution. You will be called on for a wide range of responsibilities, from data aggregation, scraping, validation, transformation, quality and devops administration of both structured and unstructured datasets. Ideally, you will be experienced in optimizing data architecture, building data pipelines and wrangling data to suit the needs of our algorithms and application functionality. You also must have deep experience in data security while making it accessible via our API. Since you’ll be joining an early-stage startup at the ground level, you’ll need to be a self-starter with a high degree of initiative and accountability. You must be able to wear multiple hats and take on additional responsibility on our growing team.
Rustle’s mission is to create the most effective way for customers and companies to interact, leveraging AI, natural-language processing, and a mobile-first interface. We believe the outdated model of the customer contact center, and its huge IT and organizational cost, that has been in-place for over 50 years is due for a reset. We believe the existing model is frustrating and demotivating for both customers and customer service agents. We believe customers want a faster, easier, more satisfying way to interact with companies; and that companies want a less expensive, more transparent, and more flexible way of nurturing their customer relationships. We believe that if companies and customers could design their ideal way of communicating, that it would not involve contact centers, CRM systems and case numbers, but a seamless, personalized, empowered experience. Rustle is building that experience.
Specific Responsibilities Include:
* Create and maintain optimal data pipeline architecture across multiple data sources, including licensed and scraped data. * Assemble large, complex data sets that meet functional needs of AI/ML engineers and front-end engineers.
* Design and develop optimal data processing techniques: automating manual processes, data delivery, data validation and data augmentation.
* Develop any necessary ETL processes to optimize analysis and performance.
* Manage analytics tools that provide actionable insights into usage, customer acquisition, operational efficiency and other key business performance metrics.
* Design and develop a RESTful API to enable programmatic integration to other SaaS systems.
* Architect and implement new features from scratch, partnering with our AI/ML engineers to identify data sources, gaps and dependencies.
* Identify bugs and performance issues across the stack, including performance monitoring and testing tools to ensure data integrity and quality user experience.
* Build a highly scalable infrastructure using SQL and AWS big data technologies.
* Keep our data secure and compliant with international data handling rules.
What You Must Bring:
* Must Haves:5+ years professional experience shipping high-quality, production-ready code.
* Strong computer science foundations, including data structures & algorithms, OS, computer networks, databases.
* Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
* Experience in setting up data pipelines using relational SQL and NoSQL databases, including Postgres, Cassandra and MongoDB.
* Experience with AWS cloud services, including S3, EC2, EMR, RDS, Redshift.
* Proven success manipulating, processing and extracting value from large heterogeneous datasets.
* Strong analytic skills related to working with unstructured datasets.
* Experience with extracting and ingesting data from websites using web crawling tools.
* Experience with big data tools, including Hadoop, Spark, Kafka, etc.
* Experience developing scalable RESTful APIs.
* Expertise with version control systems, such as Git.
* Excellent communication skills and the ability to have in-depth technical discussions with both the engineering team and business people.
* Excellent English language skills.
* Self-starter and comfort working in an early-stage environment.
* Strong project management and organizational skills.
Nice to Haves:
* BSc in Computer Science, Mathematics or similar field; Master’s or PhD degree is a plus.
* Understanding of AI/ML models.
* Experience with consumer applications and data handling.
* Familiarity with data privacy regulations and best practices.
Accountability: an obligation or willingness to accept responsibility or to account for one's actions while doing so with the highest regard for integrity.
Leadership: able to influence others to follow you and lead the team to a brighter future.
Grit. able to stick with projects and work hard through good and bad times. High pain tolerance and can perform well under stress or pressure.
Scrappy: Takes initiative and proactively gets things done with low resources, but doing creative things, begging, borrowing, and whatever is needed in an ambiguous environment or situation.
Ownership orientation: Demonstrated orientation of extreme ownership over all aspects of the company and extremely results-driven in nature.
Solution Oriented: Helps to identify the source of a question or challenge and provide the right, or a better, way of doing things.