Mandatory Key skills:
?
Primary skill required for the data engineer role is hands-on experience with
Spark, particularly PySpark.
? Candidates must have experience in coding data pipelines in Spark and
should be comfortable with Python for automation.
? Other skills like Azure, Airflow, and Databricks are good to have but not
mandatory.
? 1 Coding Challenges in Interviews: candidates must be comfortable with
hands-on coding during the interview process.
? They should be able to write code in PySpark or Scala Spark and should have
built and productionized data pipelines. This is crucial for the data engineer
role.
JD:
Job Location: Pune (KharadI)
JC : 96706
3Open Position
NP: Immediate Joiner or 30Days
Experience:
5-10 years of hands-on experience in the data analytics space as a data engineer.
Familiar with ETL, DQ, DM, and reject and recycling concepts.
A significant portion of this experience should involve building data analytics
solutions in a big data environment using Hadoop clusters or cloud environment.
Technical Skills:
Extensive experience in building data pipelines using Spark, particularly PySpark.
Candidates must have a minimum of 3 years of hands-on experience in coding
with PySpark applications using RRDs, DataFrames & datasets and NOT Spark
SQLs.
Candide should has developed numerous spark application for various use cases
of processing large volumes of data, used performance tuning, works extensively on
complex transformation skills using group, window,
Publi
c
Candidate who has participated in PySpark code hackathon
Please apply only if you are confident in writing decent PySpark code during the
interview.
Strong proficiency in Python.
Write clean, efficient, and reusable Python code
Identify, troubleshoot, and fix bugs in programs to ensure code qualit
Creating scripts and tools to automate tasks and processes
Note: This role requires advanced Python coding skills, not just basic knowledge
or simple coding experience. Candidates will be required to demonstrate their
Python skills during the interview.
Familiarity or exposure to tools such as Airflow, Databricks, and Azure is a plus, but
not mandatory. The primary focus is on Spark, PySpark, and data engineering.
Additional Skills:
Strong problem-solving and analytical abilities.
Ability to comprehend business requirements and translate them into technical
solutions.
Good communication and collaboration skills to work effectively with team members.
Familiarity with the software development lifecycle, including CI/CD pipelines.
Experience working in an Agile environment.
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