Data Engineer Analog and Digital Labs Payroll | 15 - 25 Lakh/Year INR | Fully Remote | IN

Description

I.          POSITION OVERVIEW:

 

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

 

 

II.       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, and 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 BE sites.

 

 

 

 

III.     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 the 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

Position

Data Engineer

Expertise

Java (All Versions) - 4 years

C++ - 4 years

SQL - 4 years

NoSQL - 4 years

Apache-Kafka - 5 years

Nifi - 5 years

Apache Spark - 5 years

Data Engineer - 4 years

PowerBI - 4 years

Apache Scala - 4 years    

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