● Highly proficient with object-oriented programming and writing production-grade and
● Highly proficient with python data science stack (e.g. numpy, pandas, scipy, scikit-learn,
gensim, jupyter notebook, dash, streamlit etc.)
● Experience with Python API design and implementation with Flask, FastAPI, gunicorn etc.
● Knowledge of relational SQL and NoSQL databases, including Mongodb, ElasticSearch,
Snowflake, MySQL, Cassandra, etc.
● Experience with containerization tech such as Docker, docker-compose, kubernetes (k8s).
● Experience with cloud products such as AWS, GCP, PubSub, Dataflow, Cloud Run etc.
● Familiar with DataVis products such as Power BI, , Superset etc.
● Experience with big data tools: Hadoop, Spark, Kafka, Kinesis etc.
● Extensive experience with data pipelines and workflow management tools: Azkaban, Luigi,
NiFi, Airflow, etc.
● Previous exposure to stream-processing systems: Storm, Spark-Streaming, Flink etc.
● Experience with ML feature store design and implementation
● Experience with ML experiment tool such as Clear ML, Weight & Bias or other equivalents