DashLX is seeking a critical thinker and self-starter to assist with vendor integrations, data pipeline optimization, and scalable data infrastructure. This is a unique opportunity to work with a small startup, utilizing cutting-edge cloud service technologies to enhance data processing and analytics.
For this position, we are seeking a senior-level data engineer who is experienced in Python, Java, and cloud-based data pipelines. The ideal candidate will be responsible for integrating vendors via OAuth1/2, maintaining streaming data applications, and optimizing our AWS-based data infrastructure.
DashLX is not currently sponsoring applicants for work visas.
Develop and maintain secure vendor connections using OAuth1/2 protocols.
Write and optimize Python code with FastAPI for seamless integrations, deployed via AWS Lambda and API Gateway v2.
Update and maintain our Apache Flink application in Java to parse, process, and map incoming data.
Ensure that data streams from Kinesis are correctly ingested and transformed into Apache Iceberg tables on S3.
Work closely with cross-functional teams to improve data workflows and integration processes.
Troubleshoot, monitor, and optimize the performance of data ingestion and processing pipelines.
Act as a subject matter expert (SME) for data engineering best practices within the organization and for clients.
Provide occasional insights on native app development (experience with Apple HealthKit and Google Fit is a strong plus).
Ensure your home work environment is adequate to carry out your responsibilities. (e.g., work computer, internet connection, phone, etc.)
We are a mostly distributed workforce; therefore, you will likely be required to work from home. Hours are flexible, though you will need to be available at some point between 8-5 Central Time for meetings.
BENEFITS
Competitive salary and comprehensive benefits (healthcare, PTO, etc.).
Flexible working hours with a fully remote work environment.
Stock options based on performance and company growth.
Opportunity to work in a fast-paced, innovative environment with room for professional growth.
Be part of a dynamic team building innovative SaaS solutions from the ground up.
Collaborate closely with experienced leaders who value creativity, autonomy, and technical excellence.
Shape the future of our cloud services while growing your career in Data Engineering.
Formal Computer Science degree in programming, algorithms, data structures, systems design, and computational theory.
6+ years of experience in data engineering or related fields.
Strong proficiency in Python, particularly with FastAPI, and experience deploying applications on AWS Lambda and API Gateway v2.
Demonstrated expertise with OAuth1/2 protocols for vendor integrations.
Solid experience in Java and hands-on work with Apache Flink.
Familiarity with AWS Kinesis (managed Flink and stream processing) and data storage solutions like Apache Iceberg on S3.
Excellent problem-solving skills, with a keen ability to optimize and troubleshoot data pipelines.
Strong communication and collaboration skills to work effectively with technical and non-technical teams.
Experience in native mobile app development (e.g., integrating with Apple HealthKit or Google Fit).
Familiarity with CI/CD practices for data engineering projects.
Experience with modern data processing architectures and a passion for scalable, high-performance systems.
On a scale of 1-4, where 1 = little to no prior experience, 2 = moderate experience and excited to learn more, 3 = considerable experience and 4 = mastery, how would you rank yourself with these technologies and methodologies: