Job Summary
Synechron is seeking an experienced PySpark Data Engineer / Data Scientist to lead data pipeline development and advanced analytics initiatives within our financial data and index analytics division. This role plays a crucial part in building scalable data processing solutions, enabling data-driven insights, and supporting machine learning workflows in both batch and streaming settings. The ideal candidate will possess a robust technical foundation in big data processing, analytics, and software engineering, along with leadership capabilities to drive impactful data projects.

Software Requirements

Required Skills:
Proven expertise in Python programming, emphasizing clean, maintainable, and scalable code
Hands-on experience with PySpark in both batch and streaming workflows
Deep knowledge of data manipulation and feature engineering, including Pandas, NumPy, and visualization libraries (matplotlib, seaborn)
Experience with Spark components like Spark SQL, DataFrames, and Spark MLlib
Familiarity with data storage solutions: SQL and NoSQL databases (e.g., Hive,



Cassandra)
Knowledge of ETL tools such as Apache Airflow, Jenkins, or GithHub Actions for scheduling and automation
Experience working with cloud environments, especially Azure or AWS for big data processing

Preferred Skills:
Hands-on with containerization and orchestration (Docker, Kubernetes)
Exposure to distributed storage solutions like Hadoop HDFS or Azure Data Lake

Overall Responsibilities
5 years of experience in Design, develop, and optimize large-scale data pipelines using PySpark for structured, semi-structured, and unstructured data
5 years of experience to Lead the building of ML pipelines for training, validation, and deployment of models in streaming/batch modes
Write high-quality, productive code that supports data transformation, cleaning, and feature engineering
Collaborate with data scientists, analysts, and stakeholders to understand data requiremen

📌 Pyspark Data Engineer Big Data Bengaluru
🏢 Synechron
📍 Bengaluru