At least 8+ years of strong data warehousing experience using RDBMS and Non-RDBMS databases.
At least 5 years of recent hands-on professional experience (actively coding) working as a data engineer (back-end software engineer considered). Professional experience working in an agile, dynamic and customer facing environment is required.
Understanding of distributed systems and cloud technologies (AWS) is highly preferred.
Understanding of data streaming and scalable data processing is preferred to have.
Experience with large scale datasets, data lake and data warehouse technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake is highly preferred.
Atleast 2+ years of experience in ETL (AWS Glue), Amazon S3, Amazon RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step Functions.
Strong knowledge in scripting languages like Python, UNIX shell and Spark is required.
Understanding of RDBMS, Data ingestions, Data flows, Data Integrations etc.
Technical expertise with data models, data mining and segmentation techniques.
Experience with full SDLC lifecycle and Lean or Agile development methodologies.
Knowledge of CI/CD and GIT Deployments.
Ability to work in team in diverse/ multiple stakeholder environment.
Ability to communicate complex technology solutions to diverse teams namely, technical, business and management teams.
