Job Description:Summary:
The Sr. Analytics engineer is responsible for delivery 
of software modeling and data science solutions. This 
role will lead the design, development and 
operationalization of state-of-the-art machine learning 
based solutions. Assist or conduct problem studies 
leading to recommendations for upgrading/improving 
existing equipment in field or lab environment. Performs 
product-testing functions in a test lab facility and/or 
field location. 
Job Duties/Responsibilities 

• Serve as chief architect for data analytics and

machine learning 

• Perform architecture design and implementation of

IoT and Big Data 

• Develop highly scalable and extensible Big Data

platforms which enable collection, storage, 
modeling, and analysis of massive data sets 
including those from IoT and streaming data 

• Effectively communicate complex technical concepts

to non-technical business and executive leaders 

• Assist with scoping, pricing, architecting, and

selling large project engagements 

• Responsibility for coordinating engineering work

assignments and making recommendations on technical 
application developed by other professional 
personnel or consultants. 

• Provides guidance and training to less experienced

staff. 

• As a specialist, conducts special, complex and

advanced level studies 

Job Requirements:
Skills/Knowledge 

• Advanced expertise in data analytics and machine

learning 

• Experience in Matlab Simulink
• Experience in physics modeling
• Demonstrated experience of architecting and

implementing IoT architecture and analytical systems 
in various project scenarios 
* 
Hands-on experience with cloud platform 
technologies: Microsoft Azure IoT / Analytics Suite 
* 
Streaming data tools and techniques such as Kafka, 
Azure Streaming Analytics, AWS Kinesis 
* 
Experience with cloud gateways, queues, messaging 
hubs such as Azure Event Hub, Azure IoT Hub, MQTT, 
XMPP, CoAP 
* 
Engineering and/or software development experience 
and demonstrable architecture experience at 
enterprise scale 
* 
Prior technology consulting experience desired 
* 
Experience in architecture and implementation of 
large and highly complex projects 
* 
History of working successfully with 
cross-functional engineering teams 
* 
Experience with Big Data platforms e.g. Azure DW, 
SQL PDW, Cloudera, Hortonworks 
* 
Visualization experience: PowerBI, Tableau 
* 
Big Data Analytic frameworks and query tools such 
as: HDINsight, Spark, Storm, Hive, Impala 
* 
ETL (Extract-Transform-Load) tools such as 
Microscoft SSIS, Azure Data Factory, Pentaho PDI or 
Talend or Informatica; also experience with ELT 
* 
Continuous delivery and deployment using Agile 
Methodologies. 
* 
Data Warehouse and DataMart design and 
implementation 
* 
NoSQL environments such as Cosmos, MongoDB, 
Cassandra & Blob Storage 
* 
Data modeling of relational and dimensional 
databases 
* 
Metadata management, data lineage, data governance, 
especially as related to Big Data 
* 
Structured, Unstructured, Semi-Structured Data 
techniques and processes 
* 
Machine Learning (R, Scala, Python) 
Education 
Bachelor's degree in a technical field such as Computer 
Science, Mathematics, Physics, Engineering. Master's 
degree or higher preferred 
Experience 

• 10+ years with engineering discipline
• 5+ years with reliability analytics
• FMECA / FMEA
• Reliability, availability and maintainability (RAM)

analysis 

• Life data analysis
• Reliability predictions