Sr Data Engineer

Development, maintenance, and enhancement of Data Pipelines (ETL/ELT) and processes with thorough knowledge of star/snowflake schemas Hands on experience in Power. Center Developer/IDMC/IICS Data Integration Experience in DW Production Support / troubleshooting data or pipeline issues Developing complex SQL queries and SQL optimization Development experience must be full Life Cycle experience including business requirements gathering, data sourcing, testing/data reconciliation, and deployment within Business Intelligence/Data Warehousing Architecture.

Designing and implementing data security Monitoring and optimizing data storage and data processing Use of Object function/object-oriented scripting languages including Scala, C++, Java and Python Cloud data warehouse and data lake platforms (e.g., Snowflake, Databricks, Redshift, Big. Query, MS Synapse, MS ADLS, Apache Haddop, etc.)

Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. Strong project management and organizational skills. Experience supporting and working with cross-functional teams in a dynamic environment. Understanding of data science concepts Familiarity with AI/ML frameworks and libraries Requirements

• Developing data services that are fit for purpose, resilient, scalable, and future proof, to meet user needs
• Advanced SQL knowledge and experience working with relational databases and working familiarity with various databases.
• Demonstrated understanding and experience using software and tools including ETL, relational SQL and NoSQL databases, big data tools like Kafka, Spark, and Hadoop
• Experience building and optimizing ‘big data’ data pipelines, architecture, and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Experience and knowledge of project management best practices and agile software development methodologies
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Understanding of data science concepts
• Familiarity with AI/ML frameworks and libraries