At least 8+ years of extensive experience in data warehousing using both RDBMS and non-RDBMS databases
Minimum of 5 years of recent hands-on professional experience as a data engineer (backend software engineer also considered), actively involved in coding
Professional experience in an agile, dynamic, and customer-facing environment is required
Strong understanding of distributed systems and cloud technologies, with preference given to experience with AWS
Preferably experienced in data streaming and scalable data processing
Experience with large-scale datasets, data lake, and data warehouse technologies such as AWS Redshift, Google Big Query, and strongly preferred is Snowflake
Minimum of 2+ years of experience in Amazon RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step Functions
Demonstrated expertise in scripting languages like Python, UNIX shell, and Spark is required
Understanding of RDBMS, data ingestion, data flows, and data integrations, among others
Technical proficiency in 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 effectively in a diverse, multiple stakeholder environment
Ability to effectively communicate complex technology solutions to various teams, including technical, business, and management teams
Requirements
Work with stakeholders to understand needs for data structure, availability, scalability, and accessibility
Develop tools to improve data flows between internal/external systems and the data lake/warehouse
Build robust and reproducible data ingest pipelines to collect, clean, harmonize, merge, and consolidate data sources
Understanding existing data applications and infrastructure architecture
Build and support new data feeds for various Data Management layers and Data Lakes
Evaluate business needs and requirements
Support migration of existing data transformation jobs in Oracle, and MS-SQL to Snowflake
Ability to write oracle sql, PLSQL scripts and should have demonstrated working experience in managing the oracle scripts
Should have a good hands on with linux scriptings
Able to document the processes and steps
Develop and maintain datasets
Improve data quality and efficiency
Lead Business requirements and deliver accordingly
