As a Senior Analytics Engineer, you will be responsible for the design, development and monitoring of data products (especially feature store), packages and processes that will help streamline the creation and deployment of data science solutions made by our Data Scientists.
NATURE OF WOR
- KWork with our Data Scientists to design datasets that are useful for creating statistical and machine-learning model
- sDesign, develop and maintain feature stores as well as the accompanying feature pipelines that will be used in creating training data as well as real-time inference features
- .Implement data quality and integrity checks and ensure the quality and availability of data sources in accordance with their SLAs
- .Align with Data Engineering and Data Governance team to achieve maturity in the data
- .Create and maintain software packages for use by our Data Scientists to help improve their model development workflow
- .Build CI/CD pipelines and microservices, to improve time to deployment and proactively catch issues before they hit productio
- nProvide guidance on best practices for code and architecture of data pipelines and microservices, and do code and architecture reviews to ensure adherence to best practice
- sCommunicate technical architecture and solutions, as well as explain the competitive advantage of various technologies to a broad audienc
- eCreate and maintain architecture and systems documentatio
n
NICE TO HA
- VEHigh proficiency in Data Warehouses (Redshift, Databricks, etc) and manipulating data within them (using SQL or Spark
- ).High proficiency in the design, development, and monitoring of ETL pipelin
- esModerate experience (at least 2 years) in working with AWS or any Cloud providers (such as GCP or Azure
- ).Moderate experience in creating and evangelizing best practices and too
- lsModerate experience in interacting with different stakeholders at different level
- s.Some experience (at least 1 year) with common data science tools, packages (Pandas, SKLearn), and concep
- tsGood programming skills (Python, R, Bash scripting, or any languages for ETL pipeline
- s)Moderate Experience working in an Agile, Dev Ops, Test Driven Development environme
- ntExperience in designing, developing, and optimizing ML Feature Store is a plu
- s.Experience in working with Sagemaker is a plu
- s.Experience in building CI/CD pipelines and data testing for data integrity and correctness is a plu
- s.Experience with building streaming applications using Kafka, Kinesis, or other message queues is a plu
- s.Experience with using Data Build Tool (DBT) for ETL is a pl
us
REQUIRED QUALIFICATI
- ONSWith at least a bachelor's degree in any quantitative discipline (i.e. Computer Science, Math, Physics, e
- tc)Having at least 5 years of experience in creating building and maintaining ETL pipeli
- nesHaving at least 1 year of experience in managing stakehold
ers
