Hadoop Developer

Responsibilities include: 

• Convert the machine learning models into application program interfaces (APIs) so that other applications can use it
• Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what results they gain from the model
• Build data ingestion and data transformation infrastructure
• Automate infrastructure that the data science team uses
• Perform statistical analysis and tune the results so that the organization can make better-informed decisions
• Set up and manage AI development and product infrastructure
• Be a good team player, as coordinating with others is a must

• At least 4 to 7 years of relevant experience as Big Data Engineer
• Hands-on experience in Scala or Python
• Hands-on experience on major components in Hadoop Ecosystem like HDFS, Map Reduce, Hive, Impala.
• Strong programming experience in building applications/platform using Scala or Python.
• Experienced in implementing Spark RDD Transformations, actions to implement business analysis

Job Description:

The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible. 

Our ideal candidate

The role would be a client facing one, hence good communication skills are a must. 

The candidate should have the ability to communicate complex models and analysis in a clear and precise manner. 

The candidate would be responsible for:

• Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
• Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
• Understanding the math behind algorithms and choosing one over another
• Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy

Desired technical requirements

• Proficiency with Python and the ability to write production-ready codes. 
• Experience in pyspark, machine learning and deep learning
• Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
• Familiarity with SQL or other databases.

Roles and Responsibilities

• KSQL
• Data Engineering spectrum (Java/Spark)
• Spark Scala / Kafka Streaming
• Confluent Kafka components
• Basic understanding of Hadoop

Primary responsibilities:

• Architect, Design and Build high performance Search systems for personalization, optimization, and targeting
• Designing systems with Solr, Akka, Cassandra, Kafka
• Algorithmic development with primary focus Machine Learning
• Working with rapid and innovative development methodologies like: Kanban, Continuous Integration and Daily deployments
• Participation in design and code reviews and recommend improvements
• Unit testing with JUnit, Performance testing and tuning
• Coordination with internal and external teams
• Mentoring junior engineers
• Participate in Product roadmap and Prioritization discussions and decisions
• Evangelize the solution with Professional services and Customer Success teams