Proficiency in Python or Java programming languages.
Hands-on experience with Big Data technologies like Hadoop and Apache Spark.
Strong SQL skills and experience with data querying tools such as Hive, Impala, or Presto.
Educational background in Computer Science, Data Engineering, or related fields.
Requirements:
Build and optimize big data pipelines and architectures.
Develop processes for data transformation, ingestion, and validation.
Collaborate with business teams to understand requirements and resolve technical challenges.
Work closely with solution architects on system and interface design.
Job description
Hi to all Tech Enthusiasts out there , We are hiring for a reputed IT client of ours for the below positions :
Expertise and handson experience on PythonJava, Bigdata, Apache Spark, Hadoop
(*Mandatory*)
Designation: Software Engineer
Good to Have:
• Good to have exposure of Hadoop Data Lakes created using these distribution (Cloudera, Horton Works, MapR, EMR, HDInsight, DataProc)
• Exposure of the Analytics stack of any Public Cloud (AWS, Azure, GCP) will be good to have.
Experience:
5 to 12 Years
Notice Period : 15 to 20 Days
Responsibilities
• Strong expertise in SQL
• Strong expertise in one or more Big Data Querying technologies Hive, SparkQL, Impala, Presto, Phoenix
• Strong analytical, problemsolving, data analysis and research skills.
• Ability to work with various business teams to resolve technical challenges and understand requirements.
• Demonstrable ability to interact, collaborate, drive consensus and confidence among different (of our) groups – both onshore and offshore.
• Demonstrable ability to think outside of the box and not be dependent on readily available tools.
Qualifications
Roles:
• Build and optimize ‘big data’ pipelines, architectures and data sets.
• Build processes supporting data transformation, data structures, data ingestion, metadata, dependency and workload management.
• Should be able to understand, create, modify and optimize SQLs.
• Should be able to work on SQL engines, Cloud Data warehouses
• Should be able to perform data validation
• Should be able to automate SQL transformations in the product.
• Work closely with Solution Architect Architect to drive solutions architecture, systems and interface design, data analysis, scenario and use case analysis)
Good to have:
• Hands on exposure of Hadoop Data Lakes created using these distribution (Cloudera, HortonWorks, MapR, EMR, HDInsight, DataProc)
• Exposure of the Analytics stack of any Public Cloud (AWS, Azure, GCP) will be good to have.
