Senior Data Engineer - SRKay Consulting Group

1. POSITION OVERVIEW:

Data engineer is part of central factory automation group for all of its Back End sites. Analytics and decision making is a key strategy for factory automation and data engineering is responsible for curation of data in the data lake , creating data pipelines to catre the request from the BI appplication team and the data science team. Understanding and integrating the data from multiple source systems to the data lake implementation. Creating the sufficient documents including but not restricted to the pipeline design spec, dfd and associated details. Data engineer is also responsible for building data pipelines adhiring the industrial standards and also creating reusable frameworks in the system to enable performant computing.

1. 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 across company's BE sites.

1. SKILLS /COMPETENCIES

(Top 3-7 most important/critical competencies needed for the job both soft and hard skills):

• 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 unserstanding of how to transform and connect the data of various types and form
  • Great 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.