• Design, build and operationalize large scale enterprise data solutions using cloud services and open source big data technologies (on-premise stack)

• Develop processes for data pipeline, data modeling, and data production

• Develop, test, and maintain architectures, build data systems and pipelines

• Collaborate with teams in different verticals (eg, data architect, data scientist/Operations Research, sales) on the projects goals

• Develop sophisticated analytics programs, ML, and statistical methods

• Knowledge of programming languages (e.g. Java, Scala, Python)

• Great numerical, analytical, and programming skills

• Apache Spark, Hadoop, MapReduce

• Data warehouse, Data Lake, Data modeling, Database design

• Evaluate business needs and objectives; Build algorithms and prototypes

• Open source stack: Hadoop, HDFS, Spark, Storm, Kafka, Flume, Airflow

• AWS Stack – DynamoDB, Redshift, Data Lake, S3, Athena, Glue PySpark, EMR, Kinesis, Lambda

• DB: Elasticsearch, MongoDB, Cassandra, MySQL/PostgreSQL, NoSQL, Hive

• Visualization tools: Tableau, AWS Quicksight, Kibana, Grafana

NOTES

• 5+ years experience preferred; Degree/Masters in Computer Science, IT, or similar field

• Remote working / working from co-working spaces occasionally

• Willingness to travel an add-on

• Knowledge and experience in licensed big data stack is a plus

• Data Stack exposure to hybrid cloud platforms are also value adds