Proven experience with Python or Java and Big Data technologies like Hadoop and Spark.
Strong educational background in computer science or related fields.
Hands-on experience with data lakes and cloud analytics platforms (AWS, Azure, GCP) is advantageous.
Excellent problem-solving and analytical skills with the ability to collaborate across teams.
Requirements:
Build and optimize big data pipelines and architectures.
Develop processes for data transformation, ingestion, and management.
Collaborate with business teams to understand requirements and resolve technical challenges.
Perform data validation and automate SQL transformations.
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 : Big Data Developer Lead Associate Architect.
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 : 12 to 18 Years
Notice Period : Immediate or 15 to 30 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.
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)
