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We are looking for a skilled Senior Developer with strong expertise in PySpark to design, build, and maintain scalable data processing solutions.
The ideal candidate will have experience working across the data engineering stack, strong knowledge of distributed computing, and hands-on exposure to SDLC-based project development.

We are seeking an experienced Python Backend Developer to design, build, and maintain scalable backend systems and APIs.
The ideal candidate has strong expertise in Python frameworks, database design, and backend performance optimization.
We are looking for a DevOps Engineer to build, automate, and maintain scalable, secure, and highly available infrastructure.
The ideal candidate has strong experience in cloud platforms, CI/CD automation, and modern DevOps practices.

Key Responsibilities:

Design, develop, and optimize large-scale data pipelines using PySpark.
Build and maintain ETL/ELT workflows to process structured and unstructured data.
Work with big data technologies such as Hadoop ecosystem, Spark, and Impala.
Collaborate with cross-functional teams including data scientists, analysts, and product teams.
Ensure code quality through best practices, code reviews, and version control.
Optimize job performance, memory management, and execution time in Spark jobs.
Work on data modeling, transformation, and pipeline orchestration.
Participate in end-to-end SDLC activities including requirement analysis, design, development, testing, and deployment.
Troubleshoot and resolve data processing issues and production incidents.
Contribute to automation, monitoring, and logging frameworks.
Required Skills and Qualifications:
Strong hands-on experience with Python and PySpark (mandatory).
Strong SQL skills including advanced querying and performance tuning.
Experience with distributed data systems such as Hadoop and Spark ecosystem.
Experience with Impala, Hive, and SQL Server or other relational databases.
Strong understanding of data structures, algorithms, and performance optimization.
Experience with ETL pipeline development and data warehousing concepts.
Knowledge of SDLC methodologies (Agile/Scrum preferred).
Familiarity with version control systems such as Git.
Experience working with large datasets in production environments.
Knowledge of C# or other programming languages.
Experience with cloud platforms such as Azure, AWS, or GCP.
Exposure to workflow orchestration tools like Airflow or Oozie.
Understanding of data lakes, data governance, and data quality frameworks.
Experience with CI/CD pipelines.
Strong analytical and problem-solving abilities.
Good communication and collaboration skills.
Ability to work independently and in a fast-paced environment.
Proactive mindset with attention to detail.
Preferred Candidate Profile:
6-10 Years of Hands-on PySpark developer with real-time project delivery experience.
Bacheler’s degree in any specialization
Exposure to end-to-end data pipeline lifecycle.
Comfortable handling large-scale data processing and optimization challenges.

Apply Now

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