6 + YoE - Data Engineer – Big Data / PySpark - any UST Location - Immediate Joiner
Summary
Data Engineer building and optimizing Big Data pipelines with PySpark, Apache Spark, Airflow, and Python, including Spark performance tuning and CI/CD integration on cloud platforms (GCP preferred).
Candidates ready to join immediately can share their details via email for quick processing.
CCTC | ECTC | Notice Period | Location Preference
nitin.patil@ust.com
Act fast for immediate attention! ⏳
Must-Have Skills
- 6+ years of overall experience in Data Engineering / Big Data.
- Strong understanding of Big Data concepts and architecture.
- Strong hands-on experience with Apache Spark.
- Expertise in:
- Spark Performance Tuning
- Spark Optimization
- Query/Job Performance Improvement
- Troubleshooting Spark workloads
- Strong hands-on experience with PySpark and Spark.
- Strong programming experience in Python.
- Good experience working with MySQL / SQL.
- Strong experience in designing and developing Data Pipelines.
- Hands-on experience with Apache Airflow for data pipeline orchestration and scheduling.
- Experience working with at least one Cloud Platform.
- GCP experience is preferred.
- Good understanding of CI/CD and DevOps concepts.
- Experience integrating data engineering workloads with CI/CD pipelines.
- Strong debugging, troubleshooting, and problem-solving skills.
Preferred Skills
- Hands-on exposure to relevant GCP data services.
- Experience handling large-scale and high-volume datasets.
- Understanding of distributed data processing and data architecture.
- Experience improving the scalability, reliability, and performance of data pipelines.
- Exposure to Agile development and DevOps practices.
Key Responsibilities
- Design, develop, and maintain scalable Big Data and Data Engineering solutions.
- Develop data processing applications using Python, PySpark, and Apache Spark.
- Perform Spark performance tuning and optimization for large-scale workloads.
- Build, maintain, and monitor robust ETL/ELT data pipelines.
- Develop and manage workflow orchestration using Apache Airflow.
- Work with MySQL/SQL for data extraction, transformation, and validation.
- Deploy and support data engineering solutions in cloud environments, preferably GCP.
- Work with DevOps teams to implement and maintain CI/CD pipelines.
- Troubleshoot production issues and optimize data processing performance.
- Collaborate with engineering and business teams to deliver reliable and scalable data solutions.
Primary Skill Combination
Big Data + Apache Spark + PySpark + Python + Airflow + SQL/MySQL + Cloud (GCP Preferred) + CI/CD
Mandatory Focus: Strong hands-on Apache Spark performance tuning and optimization experience.