Data Engineer

Developing telemetry software to connect Junos devices to the cloud

Fast prototyping and laying the SW foundation for product solutions

Moving prototype solutions to a production cloud multitenant SaaS solution

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources

Build analytics tools that utilize the data pipeline to provide significant insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with partners including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Work with data and analytics specialists to strive for greater functionality in our data systems.

Qualification and Desired Experiences

Master in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background

5+ years experiences building data pipelines for data science-driven solutions

Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning model

Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow

Good team worker with excellent interpersonal skills written, verbal and presentation

Create and maintain optimal data pipeline architecture,

Assemble large, sophisticated data sets that meet functional / non-functional business requirements.

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Experience with AWS, S3, Flink, Spark, Kafka, Elastic Search

Previous work in a start-up environment

3+ years experiences building data pipelines for data science-driven solutions

Master in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background

We are looking for a candidate with 9+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

Experience with big data tools: Hadoop, Spark, Kafka, etc.

Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.

Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.

Experience with AWS cloud services: EC2, EMR, RDS, Redshift

Experience with stream-processing systems: Storm, Spark-Streaming, etc.

Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning model

Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow

Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.

Experience performing root cause analysis on internal and external data and processes to answer specific business questions and find opportunities for improvement.

Strong analytic skills related to working with unstructured datasets.

Build processes supporting data transformation, data structures, metadata, dependency and workload management.

A successful history of manipulating, processing and extracting value from large disconnected datasets.

Proven understanding of message queuing, stream processing, and highly scalable ‘big data’ data stores.

Strong project management and interpersonal skills.

Experience supporting and working with multi-functional teams in a multidimensional environment.