About the Engineering Organization:
Having already assembled an exceptionally skilled and passionate team of developers and data scientists, we are looking for world-class engineers who want to take location-data understanding to a new frontier, where it connects with real-world behavior. We love building regression models, classification algorithms, data visualizations, and geo-spatial clustering, within our location-data platform, which processes terabytes of data daily to generate the fundamentals of location-data products. PlaceIQ Engineers live for huge challenges and deliver in a fast paced, agile environment. Our unique culture breeds excellence and embraces creativity as we look to innovate and drive our business forward. If you have a passion for imagining and building technology solutions that will make an immediate impact in an untapped space, we want to talk to you!
At PlaceIQ, you will get the opportunity to process structured and unstructured data to extract value from it. You will be developing new data products, working alongside Data Scientists, and Product Managers, and validating the products to produce a better understanding of the real world.
The role will be to:
- Design, and develop data-products, with adjoining data-pipelines, engineered to high standards of performance, efficiency, and reliability
- Generate and implement Machine-Learning algorithms, with Data-Scientists
- Formulate data-management strategy and data-warehouse architecture to provide single source-of-truth datasets for internal and external clients
- Ensure data quality, with testing on a product and pipeline level
- Implement automation of the data pipelines & software releases
- Collaborate with internal teams to gather requirements for data-products
- Mentor data engineers to provide technical guidance
- Provide some ongoing support, monitoring, and maintenance of deployed products
- Professional development experience with Apache Spark in a Hadoop Ecosystem, preferably with Scala.
- Strong experience in building ETL/Data-pipelines.
- Background with Data-Modeling, Data-Access and Data-Warehouse technologies.
- Understanding of Machine-Learning algorithms, and computational modeling
- Experience with distributed databases e.g.: Hbase, Cassandra, MongoDB with streaming platforms e.g.: Kafka, RabbitMQ, and good-old RDBMS e.g.: PostgreSQL.
- Experience in UNIX/Linux environments with Bash/Python scripting.
- Production Continuous-Integration experience with Jenkins, and building with Maven / Ant / SBT.
- Exposure to InfluxDB, visualization with Grafana, and with schedulers e.g., Azkaban, Oozie and Airflow is a Plus.
- Experience in an Agile Scrum software development environment.
- BA/BS/MS in Computer Science/Engineering or related technical field.