01Overview
Key Responsibilities :
- Understand the factories , manufacturing process , data availability and avenues for improvement
- Brainstorm , together with engineering, manufacturing and quality problems that can be solved using the acquired data in the data lake platform.
- Define what data is required to create a solution and work with connectivity engineers , users to collect the data
- Create and maintain optimal data pipeline architecture.
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery for greater scalability
- Work on data preparation, data deep dive , help engineering, process and quality to understand the process/ machine behavior more closely using available data
- Deploy and monitor the solution
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Work together with Data Architects and data modeling teams.
Skills /Competencies :
- Good knowledge of the business vertical with prior experience in solving different use cases in the manufacturing or similar industry
- Ability to bring cross industry learning to benefit the use cases aimed at improving manufacturing process
Problem Scoping/definition Skills :
- Experience in problem scoping, solving, quantification
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores
- Ability to foresee and identify all right data required to solve the problem
Data Wrangling Skills :
- Strong skill in data mining, data wrangling techniques for creating the required analytical dataset
- Experience building and optimizing 'big data' data pipelines, architectures and data sets
- Adaptive mindset to improvise on the data challenges and employ techniques to drive desired outcomes
Programming Skills :
- Experience with big data tools: Spark, Delta, CDC, NiFi, Kafka, etc
- Experience with relational SQL ,NoSQL databases and query languages, including oracle , Hive, sparkQL.
- Experience with object-oriented languages: Scala, Java, C++ etc.
Visualization Skills :
- Know how of any visualization tools such as PowerBI, Tableau
- Good storytelling skills to present the data in simple and meaningful manner
Data Engineering Skills :
- Strong skill in data analysis techniques to generate finding and insights by means of exploratory data analysis
- Good understanding of how to transform and connect the data of various types and form
- Outstanding numerical and analytical skills
- Identify opportunities for data acquisition
- Explore ways to enhance data quality and reliability
- Build algorithms and prototypes
- Reformulating existing frameworks to optimize their functioning.
- Good understanding of optimization techniques to make the system performant for requirements. .
