ROLE: BIG DATA ENGINEER
EXPERIENCE: 4+ YEAR
JAVA, PYTHON, R, HADOOP, SPARK, CLOUDERA/MAPR/HORTONWORKS
If you aspire to create a big impact with your big data skills, lets meet-up. We work across the value chain of Bigdata and Hadoop eco-system to build and support solutions of new age, you will work with our global customers and expert teams to deliver a unique business value.
- Develop, maintain, test and support what the big data solutions architect has designed.
- Works on implementing big data projects with a focus on collecting, parsing, managing, analysing and visualizing large sets with different (NoSQL or RDBMS) databases (MongoDB, Cassandra, HBase, Hive, Pig, Impala)
- Should be able to design and develop different integration frameworks for structured, semi-structured and unstructured data.
- Effectively get involved in the solution reviews where MapR Hadoop technologies are used.
- Interface with SMEs, Big data Solution Architects, Analytics team Product managers and Domain Architects to review to-be developed solution.
- Test deliverables for build and data quality and ensure requirements are completely met.
- Be a subject matter expert in advanced analytics and an expert in our iDS Data Science bigdata landscape, toolsets and offerings.
- Should be a thinker and has the ability to solve problems independently.
- 4+ years of relevant experience.
- Any ME / M Tech / Be / B Tech with an excellent academic record.
- Machine Learning & NLP enthusiasts with good scripting and programming skills and hands-on expertise on Java, Python, R, Hadoop.
- To be proficient in designing efficient and robust ETL workflows and sound knowledge of various ETL techniques and frameworks, such as Flume.
- Good experience with Spark, Cloudera/MapR/Hortonworks. Certification will be an advantage
- Experience with various messaging systems, such as Kafka or RabbitMQ
- Good knowledge in programming / scripting languages -Java, Linux, C++, Python, Ruby.
Tools & Technologies
- Core Java, J2EE, Collections, Scala, Python
- Hadoop, HDFS, Spark, Kafka and related Big Data tools.
- DB/NoSql – MongoDB, MySql or any No SQL DB.