In a world of disruption, unpredictability, and increased expectations, companies need constant awareness of their supply chain exposure and opportunities to adapt. Traditional enterprise-centric processes leverage predominantly internal data that leads to limited visibility insights, and a reactive mode for planning and execution. Companies need to understand real-time signals from across their supply chain ecosystem and rapidly respond in a result-driven, meaningful way. ParkourSC was founded with a vision to unlock the value trapped within supply chains by synthesizing enterprise, network, and contextual data around the flow of products and assets, creating actionable insights to propel enterprise performance.
At its core, ParkourSC provides a cloud-native platform to enable digitally connected supply chains. This yields real-time visibility and intelligence to address supply chain volatility, risk, and compliance down to the product level. Having raised a Series B1 round in 2021, ParkourSC is looking to launch its 2.0 Platform in Q1 ’22 with a significant growth in customers and revenue in the coming years.
ParkourSC is seeking a passionate big-data engineer with industry expertise to join our growing data analytics & machine learning intelligence team. You will assist in interpreting the requirements of various Big Data analytics use cases and scenarios and drive the data-ops design and deliver cloud native scalable implementations of pipelines for machine learning models to drive better predictive intelligence within our platforms from a combination of external and internal data assets. You would be designing data pipelines and feature-stores for predictive recommendations, and decision engines for logistics tracking & optimizations in real time for assets in transit in close collaborations with our data-scientists, product managers and SMEs.
The ideal candidate has a proven track record in successfully delivering robust data and machine learning solutions using cloud-native technologies, with demonstrable experience in building scalable data platforms ingesting real-time IOT, de-normalizing to build OLAP friendly data-assets and managing pipeline orchestrations of engineered ML features. You will be familiar with enterprise software, cloud technology, SaaS, IoT and big data as they come together to form solutions to meet the biggest problems of customers, such as digital supply chain. You’ll thrive in a fast-paced environment and can make quick decisions. You love to build with data-pipelines & work with data-driven algorithms. You’re a technologist.
Key Responsibilities & Deliverables
- Design data-driven algorithms to infer key transportation metrics from various data sources, both ParkourSC’s own data and third-party data services.
- Contribute as a lead developer to our ML system architecture, batch & streaming data pipelines, algorithms, and machine learning techniques to build our ML intelligence tools.
- Leverage big-data delta-lake environment to integrate the MLOPs feature stores as delta lake and maintain feature pipelines.
- Research & implement fast proof-of-technology data strategies from simple SQL-driven methods to advanced ML algorithms as appropriately needed based on the task-complexity.
- Productionize the data science models at scale through a Service Oriented Architecture (SOA) by adopting modern DevOps (CICD), and continuous training (CT) principles.
- Develops and maintains data & ML engineering best practices.
- Develop and maintain a deep understanding of our data platform features and functionality and client-facing products including our underlying data models, transportation metrics, business rules validations, data-visualizations and internal APIs, and their business interpretations to client use-cases.
- Collaborate with our product managers & engineering teams to turn high-level product specifications into clean, accurate analytics and collaborate to convey them via mock-ups, exploratory data-visualizations.
Desired Skills & Experience
- Critical thinking mind who likes to solve complex problems, loves programming, and cherishes to work in a fast-paced environment.
- Strong Python development skills, with 7+ yrs. experience with SQL.
- A bachelor or master’s degree in Computer Science or related areas
- 5+ years of experience in data integration and pipeline development
- Experience in Implementing Databricks Delta lake and data lake
- Expertise designing and implementing data pipelines using modern data engineering approach and tools: SQL, Python, Delta Lake, Databricks, Snowflake Spark
- Experience in working with multiple file formats (Parque, Avro, Delta Lake) & API
- experience with AWS Cloud on data integration with S3.
- Hands on Development experience with Python and/or Scala.
- Experience with SQL and NoSQL databases.
- Experience in using data modeling techniques and tools (focused on Dimensional design)
- Experience with micro-service architecture using Docker and Kubernetes
- Have experience working with one or more of the public cloud providers i.e., AWS, Azure or GCP
- Experience in effectively presenting and summarizing complex data to diverse audiences through visualizations and other means
- Excellent verbal and written communications skills and strong leadership capabilities