Role Description The Data Engineer – PySpark (6–8 years experience) will work on a contract basis in a remote setup, designing, building, and maintaining data pipelines and data processing solutions. Day-to-day responsibilities include developing and optimizing PySpark-based ETL workflows, implementing data models, and integrating data from multiple sources into data warehouses and analytics platforms. The role involves collaborating with software engineers, data analysts, and other stakeholders to ensure data reliability, performance, and scalability for various applications.

The Data

Engineer will also monitor and troubleshoot data jobs, improve data quality, and contribute to best practices for data engineering within the organization. Qualifications

Strong Data Engineering skills, including building and maintaining data pipelines and working with large-scale data processing frameworks (preferably PySpark).

Experience with Data Modeling and Data Warehousing,



including designing schemas and optimizing data structures for analytics and reporting.

Hands-on experience with Extract Transform Load (ETL) processes, including data integration from multiple sources and automation of data workflows.

Proficiency in Data Analytics concepts, with the ability to support business intelligence and reporting teams through reliable data sets.

Solid programming skills in Python, and familiarity with distributed computing and big data ecosystems (e.g., Spark, Hadoop).

Positive understanding of relational and NoSQL databases, performance tuning, and query optimization.

Ability to work independently in a remote, contract environment, manage priorities, and communicate clearly with cross-functional teams.

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field; relevant certifications in data engineering or cloud platforms are a plus.

📌 Data Engineer - Pyspark 6-8 years exp (India)
🏢 Squash Apps
📍 India