About the role
We are looking for a talented Data Engineer to join the Data Services pod in our established Data Engineering team. As a Data Engineer on the Data Services pod, you will be instrumental in architecting and constructing a new version of the data services platform, Data Services 2.0! We operate a modern all-cloud data stack that includes AWS, Airflow, Docker, DBT, Python, Snowflake, Sigma, Java/Kotlin and our old friend SQL. If you thrive in a team environment, are willing to pitch in wherever needed to help the team succeed, are passionate about data and excited about empowering users with data to drive decision making, Roofstock is the place for you.
What you will do- Improve and maintain the data services platform.
- Deliver high-quality data services promptly, ensuring data governance and integrity while meeting objectives and maintaining SLAs for data sharing across multiple products.
- Develop effective architectures and produce key code components that contribute to the design, implementation, and maintenance of technical solutions.
- Integrating a diverse network of third-party tools into a cohesive, scalable platform, optimizing code for enhanced scalability, performance, and readability.
- Continuously improving system performance and reliability by diagnosing and resolving unexpected operational issues to prevent recurrence.
- Ensuring that your team’s work undergoes rigorous testing through repeatable, automated methods.
- Support data infrastructure and rest of the data team who designs, implements and deploys, scalable, fault-tolerant pipelines that ingest, and refine large diverse (structured, semi-structured and unstructured datasets) into simplified accessible data models in production.
- Collaborate with cross-functional teams to understand data flows and design, build and test optimal solutions for engineering challenges.
- Operate within an Agile/Scrum framework, working closely with Product and Engineering teams to deliver value across multiple services and products.
- Influence and shape the enterprise data platform and services roadmap, architecture, and design standards. Collaborate with technology leaders and team members to design, adapt, and enhance the architecture to meet evolving business needs.
- BS or MS in a technical field: computer science, engineering or similar
- 5+ years technical experience working with data
- 5+ strong experience building scalable data services and applications using either SQL, Python, Java / Kotlin, with the interest and aim to learn additional tools and technologies.
- Deep understanding of microservices architecture and RESTful API development including gRPC, REST/SOAP, GraphQL
- Experience with AWS services including Messaging such as SQS, SNS, and familiarity with real-time data processing frameworks such as Apache Kafka or AWS Kinesis.
- Significant experience building and deploying data-related infrastructure, robust data pipelines (beyond simple API pulls) & ETL/ELT code encompassing messaging, storage, compute, transformation, execution.
- Strong understanding of data architecture and related problems
- Experience working on complex problems and distributed systems where scalability and performance are extremely important (every millisecond counts)
- Experience in identifying and proposing initiatives aimed at enhancing the performance and efficiency of existing systems, setting the standard for SLAs & SLOs.
- Strong communication and interpersonal skills
- Should be independent and able to effectively work with cross functional teams
- Experience managing a team or experience working with an on-shore/off-shore model is a plus
- Knowledge of AWS and Azure cloud services.
- Previous experience in a start-up or agile environment.
- Bonus points for experience with Snowflake, Airflow
- You speak English fluently.
- You are an independent engineer (not a part of the agency) and able to work ~40 hours/week Monday-Friday and be available 9am-12pm Pacific Time Zone.
- You're committed to being available until noon Pacific time zone (not particularly working - answering in Slack and participating in occasional meetings).
- Camera and microphone are required during the interview, once hired during team meetings/discussions/etc.
- Remote work with a distributed team of engineers located across the Americas and Eurasia
