Data Engineer-(IDMC+Snowflake+SQL)

Job Summary


Responsibilities

• Development, maintenance, and enhancement of Data Pipelines (ETL/ELT) and processes with thorough knowledge of star/snowflake schemas
• Hands on experience in PowerCenter 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, BigQuery, 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.

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