JobCubby JobCubby
Sign up
Quest Global

Senior Data Engineer

Quest Global Pune, Maharashtra, India

Engineering Services · 10,001+ employees

Yesterday
data-engineer Senior (5-10 yrs) Full-time India
Create a free account to apply — email only, no card. You can also save this posting or score it against your profile with AI.

Applying here? Try the free cover letter tool — paste this posting and your résumé, no account needed.

About the role

The Senior Data Engineer will design, implement, and maintain enterprise ETL processes and scalable data pipelines using big data frameworks. They will collaborate with cross-functional teams to optimize data delivery and ensure high data quality across global client projects.

What they look for

Spark Airflow SQL PySpark Cloudera Data Platform Apache Ranger Distributed data systems Hive Metastore Data governance Iceberg Parquet ETL Data pipelines CI/CD Data validation Version control

Requirements

Candidates must have 4-6 years of experience with strong hands-on expertise in Spark, Airflow, and SQL. Proficiency in modern data platforms like Cloudera and experience with distributed data systems are essential for this role.

Full description

Job Requirements •Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.

•Develop scalable and efficient code to process data, ensuring availability and accessibility in a timely manner.

•Leverage big data processing frameworks such as Apache Spark and Hadoop to build and optimize data pipelines.

•Collaborate with senior engineers to address data challenges, contributing to solutions that maintain high data quality.

•Assist in the data delivery process, working alongside Data Engineers and Analysts to support accurate, high-value data solutions across various clients and industries.

•Build strong working relationships with team members and clients, contributing to both local and global projects.

•Learn and apply industry best practices, including version control, code reviews, and data validation, to ensure quality in data processes.

•Use SQL and other database technologies to help optimize data processing and reduce the time required to handle large data sets.

•Design, implement, and maintain data pipelines using ETL frameworks, orchestration tools, and distributed data processing engines.

•Participate in efforts to automate routine data tasks and streamline processes.

Work Experience Years of Experience: 4-6 Years

Strong hands-on expertise in Spark, Airflow, and SQL.

Deep understanding and experience with modern Data Platforms – Cloudera Data Platform (CDP)

  • Strong hands-on experience with PySpark.
  • Experience with Cloudera Data Platform (CDE, CDW, Ozone, Airflow, SDX), Apache Ranger
  • Deep understanding of distributed data systems and Hive Metastore
  • Experience and understanding of cataloging, lineage, and governance
  • Experience / understanding Open Data Contract Standard (ODCS) and its implementation
  • Experience working with SQL, file formats (Iceberg/Parquet), and partitioning/bucketing strategies.

Nice to have

  • Experience modernizing enterprise finance systems or regulated environments
  • Knowledge of CI/CD, data engineering best practices
  • Understanding of financial data structures, accounting processes, or reconciliation workflows.

Similar roles