· Development, maintenance, and enhancement of Data Pipelines
(ETL/ELT) and processes with thorough knowledge of star/snowflake schemas
· Developing complex SQL queries and SQL optimization
· Hands on experience in
PowerCenter/IDMC/IICS.
· 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.)
· 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
Requirements
- Procurement / Supplier data
- Inventory and warehouse management data
- Demand planning and forecasting
- Production orders, BOMs, routings
- Shop floor / MES data
- Quality systems (defects, CAPA,
nonconformance)
