Big data Engineer (Spark/Scala)

Wipro; Pune District; On-site; INR 3,500,000 - 5,000,000; Full time

Job summary

Wipro in Pune is seeking a senior Big Data Engineer to develop and review module-level code, create scalable data pipelines and ETL processes while delivering well-documented solutions aligned with business goals.

You should have 8-11 years of Big Data and Data Engineering experience with hands-on Python, PySpark and especially Scala, plus knowledge of Spark, Hadoop, and cloud platforms. This role operates in an Agile environment to drive robust data solutions.

Qualifications

• 8-11 years of experience in Big Data and Data Engineering.
• Strong hands-on experience in Bigdata,Python, PySpark, and Scala.
• Strong hands-on expertise in Scala (mandatory and primary skill).
• Expertise in developing scalable data pipelines and ETL processes.
• Strong knowledge of Apache Spark, Hadoop ecosystem, and distributed computing.
• Experience with data processing, performance tuning, and optimization.
• Exposure to cloud platforms such as Azure, AWS, or GCP is preferred.
• Strong problem-solving skills and experience working in Agile environments.

Responsibilities

• 8-11 years of experience in Big Data and Data Engineering.
• Strong hands-on experience in Bigdata,Python, PySpark, and Scala.
• Strong hands-on expertise in Scala (mandatory and primary skill).
• Expertise in developing scalable data pipelines and ETL processes.
• Strong knowledge of Apache Spark, Hadoop ecosystem, and distributed computing.
• Experience with data processing, performance tuning, and optimization.
• Exposure to cloud platforms such as Azure, AWS, or GCP is preferred.
• Strong problem-solving skills and experience working in Agile environments.

Skills

Big Data

Python

PySpark

Scala

Databricks

Tools

Databricks

Job description

Job description

Job Description Role Purpose

The purpose of this role is to facilitate application solutions by developing and reviewing module-level codes, creating replication patterns, performing root cause analysis to identify recurring issues and collaborating with internal and external stakeholders to ensure stable, well-documented deliverables that meet business objectives.

Job Description

• 8-11 years of experience in Big Data and Data Engineering.
• Strong hands-on experience in Bigdata,Python, PySpark, and Scala.
• Strong hands-on expertise in Scala (mandatory and primary skill).
• Expertise in developing scalable data pipelines and ETL processes.
• Strong knowledge of Apache Spark, Hadoop ecosystem, and distributed computing.
• Experience with data processing, performance tuning, and optimization.
• Exposure to cloud platforms such as Azure, AWS, or GCP is preferred.
• Strong problem-solving skills and experience working in Agile environments.

S͏kills

Mandatory Skills:Big Data, Python, PySpark,Scala.

Scala is the key skills Preferred Certification:Scala / Apache Spark / Databricks

Mandatory Skills: DataBricks - Data Engineering .

Experience: 5-8 Years .

Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.

Profile description

• 8-11 years of experience in Big Data and Data Engineering.
• Strong hands-on experience in Bigdata,Python, PySpark, and Scala.
• Strong hands-on expertise in Scala (mandatory and primary skill).
• Expertise in developing scalable data pipelines and ETL processes.
• Strong knowledge of Apache Spark, Hadoop ecosystem, and distributed computing.
• Experience with data processing, performance tuning, and optimization.
• Exposure to cloud platforms such as Azure, AWS, or GCP is preferred.
• Strong problem-solving skills and experience working in Agile environments.