*Direct Client:*

*Data Platform Engineer (AWS and Bigdata)*

*Bethesda, MD*

*6 - 12 Months*

*Start Date: ASAP*

*Rate: $80 - 85/hr all Inc*

 

*Required:*

   - The ideal candidate for our team is a thinker and a doer: someone who 
   loves algorithms and mathematical precision, but at the same time enjoys 
   implementing real systems, and is motivated by the prospect of doing 
   something never done before.
   - You will build data pipeline frameworks to automate high-volume and 
   real-time data delivery from various source channels: *AWS, GCP, Azure, 
   and a multitude of On-Premise data aggregators.*
   - Heavy use of AWS services such as: Lambda, Glue, Kafka, Kinesis, 
   Elasticsearch, Data Warehouse, Data Lakes, Analytics, Cloud Trail and Cloud 
   Watch.  
   - You will build data APIs that support critical operational and 
   analytical applications.
   - You will transform complex analytical models into scalable, 
   production-ready solutions.
   - You will continuously integrate and ship code into our cloud 
   Production environments.
   - You will work directly with Product Owners and Developers to deliver 
   data products in a collaborative and agile environment.  
   - Bring a passion to stay on top of tech trends, experiment with and 
   learn new technologies, participate in internal & external technology 
   communities, and mentor other members of the engineering community.

 

*Basic Qualifications:*

   - Degree in Computer Science, Engineering, Mathematics, Physics, or a 
   related field.
   - 3+ years experience with several of the following services building 
   modern data pipeline solutions : *AWS Lambda, Airflow, Kafka, AWS 
   Kinesis Data Streams, Data Warehouse, Data Lakes, Spark, AWS Analytics, AWS 
   Cloud Trail and AWS Cloud Watch.*
   - 3+ years experience developing software solutions to solve complex 
   business problems.
   - 3+ years experience designing, developing, and implementing data 
   pipelines and applications to stream and process datasets at low latencies.
   - 3+ years experience developing distributed systems and data 
   architecture.  Lambda design and implement batch and stream data processing 
   pipelines. Optimize the distribution, partitioning, and MPP of high-level 
   data structures.
   - 3+ years with Agile engineering practices

 

*Preferred Qualifications:*

   - Bachelor’s, Master’s or Ph.D degree in Computer Science or equivalent 
   work experience
   - 7+ years professional experience in Infrastructure development of 
   multi-threaded, scalable and highly-available distributed systems
   - Infrastructure Implementation and tuning experience in the big data 
   Ecosystem (HDP & HDF (Horton), Amazon EMR, Hadoop, Spark, R, Presto, Hive), 
   database (MariDB, mysql, postgres, Microsoft SQL Server), NoSQL (Amazon 
   DynamoDB, HBase, MongoDB, Couchbase, Cassandra), data warehousing (Netezza, 
   dashDB) or data migration and integration.
   - Infrastructure Implementation Experience with Python, Scala or Java 
   Experience working in a public cloud environment, particularly AWS 
   Familiarity with cloud warehouse tools like Snowflake Experience with 
   messaging/streaming/complex event processing tooling and frameworks such as 
   Kinesis, Kafka, Spark Streaming, Flink, Nifi, etc.
   - Infrastructure Implementation Experience with AWS technologies like 
   Redshift, S3, EC2, Data Pipeline, & EMR
   - Infrastructure Implementation Experience building RESTful API’s to 
   enable data consumption Familiarity with build tools such as Terraform or 
   CloudFormation and automation tools such as Jenkins or Circle CI 
   Familiarity with practices like Continuous Development, Continuous 
   Integration and Automated Testing Experience in Agile/Scrum application 
   development
   - Infrastructure Implementation Experience In command of setup, 
   configuration and security for Hadoop clusters using Kerberos, Ranger and 
   Ranger KMS.
   - Infrastructure Implementation Experience in implementing Deep Learning 
   frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, and Keras to help 
   our customers build DL models.
   - Infrastructure Implementation Experience in implementing SparkML and 
   Amazon Machine Learning (AML) to help our customers build ML models.
   - Infrastructure Implementation Experience with Machine Learning and/or 
   Artificial Intelligence algorithms and libraries, such as TensorFlow.
   - Infrastructure Implementation Experience in leading teams in code 
   development and balancing feature requests with feasibility constraints.

 

Warm Regards,

Pavan Pisupati | *AQUINAS**CONSULTING* <http://www.aquinasconsulting.com/>

601 Boston Post Rd #9, Milford, CT 06460

203-647-7964 | ppisup...@aquinasconsulting.com | Connect with me on LinkedIn 
<http://www.linkedin.com/in/ppisupati>

 

 

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