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Senior Data Engineer - Python/PySpark (5-8 yrs)

5-8 years

Senior Data Engineer - Python/PySpark (5-8 yrs)

Recruit Elite

posted 2mon ago

Job Description

We need candiadtes who worked on Building data pipelines heavily towards Spark - SQL. Processing over 100s of terabytes of data.ETL pipeline Data processing (Raw data processing)

What You'll Be Doing

- Build highly scalable, available, fault-tolerant distributed data processing systems (batch and streaming systems) processing over 100s of terabytes of data ingested every day and petabyte-sized data warehouse and elastic search cluster.


- Build quality data solutions and refine existing diverse datasets to simplified models encouraging self-service


- Build data pipelines that optimize on data quality and are resilient to poor quality data sources


- Own the data mapping, business logic, transformations and data quality


- Low level systems debugging, performance measurement & optimization on large production clusters


- Participate in architecture discussions, influence product roadmap, and take ownership and responsibility over new projects


- Maintain and support existing platforms and evolve to newer technology stacks and architectures

We're excited if you have :


- Proficiency in Python and pyspark


- Deep understanding of Apache Spark, Spark tuning, creating RDDs, and building data frames.


- Create Java/ Scala Spark jobs for data transformation and aggregation.


- Experience in big data technologies like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto, etc.


- Experience in building distributed environments using any of Kafka, Spark, Hive, Hadoop, etc.


- Good understanding of the architecture and functioning of Distributed database systems


- Experience working with various file formats like Parquet, Avro, etc for large volumes of data


- Experience with one or more NoSQL databases


- Experience with AWS, GCP5+ years of professional experience as a data or software engineer


Functional Areas: Software/Testing/Networking

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