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Senior Data Engineer

SEATTLE-98105, WA, US
11/28/2019

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Required Skills

Apache Spark

Company

Infinity Consulting Solutions, Inc

Experience

5 to 7 Year(s)

Job Description

Responsibilities:

Build software across platform using data processing, storage, and serving large scale web APIs, with cutting-edge technologies operating in real time with high availability.

Conduct quantitative analytics, data mining, and discovery

Come up with ways to make platform more scalable, resilient and reliable

Lead the transformation of a peta-byte scale batch-based processing platform to a near real-time streaming platform using technologies such as Apache Kafka, Cassandra, Spark and other open source frameworks

Ensure strong performance by implementing and refining robust data processing, REST services, RPC (in an out of HTTP), and caching technologies

Work closely with data architects, stream processing specialists, API developers, our DevOps team, and analysts to design systems that can scale elastically

Mentor other software engineers by developing re-usable frameworks

Review design and code produced by other engineers

Provide expert level advice to data scientists, data engineers, and operations to deliver high quality analytics via machine learning and deep learning via data pipelines and APIs

Embrace the DevOps mentality to build, deploy and support applications in cloud with minimal help from other teams.

Work with data scientists to operationalize machine learning models and build apps to make use of power of machine learning.

Qualifications:

5+ years’ experience developing with a mix of languages (Java, Scala, Python etc.) and open source frameworks to implement data ingest, processing, and serving technologies in near-time basis

Experience with big data frameworks such as Hadoop & Apache Spark, No-SQL systems such as
Cassandra or DynamoDB, Streaming technologies such as Apache Kafka

Understanding of reactive programming and dependency injection, such as Spring to develop REST services

Hands-on experience with newer technologies relevant to the data space such as Spark, Kafka, Apache
Druid (or any other OLAP databases)

Hands-on experience with developing and deploying in a cloud native environment (preferably AWS)