Principal Data Engineer/Architect

Required Skills:

·       Development, maintenance, and
enhancement of Data Pipelines (ETL/ELT) and processes with thorough knowledge
of star/snowflake schemas

·       Hands on experience in
PowerCenter/IDMC/IICS.

·       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

·       Delivering Data Solutions using Cloud Technologies

·       Advanced SQL skills and experience with relational
databases and database design like Oracle and SQLSERVER.

·       Significant experience working with cloud Data
Warehouse and Data Lake solutions (e.g., Snowflake, Redshift, BigQuery, Azure
Data Lake Storage, Amazon S3, etc.)

·       Experience working with data ingestion tools such as
Fivetran, stitch, or Matillion.

·       Working knowledge of Cloud-based solutions (e.g.,
Azure, AWS and GCP).

·       Experience building and deploying machine learning
models in production.

·       Strong proficiency in object-oriented languages:
Python, Java, C++, Scala.

·       Strong proficiency in scripting languages like Bash.

·       Strong proficiency in data pipeline and workflow
management tools (e.g., Airflow, Azkaban).

·       Familiarity with big data frameworks such as Apache
Hadoop and Apache Spark

·       Strong project management and organizational skills.

·       Excellent problem-solving, communication, and
organizational skills.

·       Demonstrated leadership experience and skills

·       Ability to communicate effectively and influence technical and business
stakeholders at all levels of the organization

Requirements

Experience in Supply Chain and
Manufacturing Domains - understand the data, the use cases, and the
value it drives rather than just the code" 

• 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)