Specialist - Data Engineering

About the role

Design, develop and maintain data pipelines using PySpark for large-scale data processing. Perform data transformations, aggregations and validations using Spark SQL DataFrames. Write and optimize SQL queries for data extraction, reconciliation and reporting. Perform data quality checks, profiling and consistency validations. Support existing data pipelines by troubleshooting failures and performing root cause analysis. Work closely with data engineers, analysts, QA and DevOps teams in Agile delivery models. Optimize performance of Spark jobs for efficiency and scalability. Maintain technical documentation, workflows and runbooks. Follow enterprise standards for coding, deployment and change management.

Responsibilities

• Design, develop and maintain data pipelines using PySpark for large-scale data processing
• Perform data transformations, aggregations and validations using Spark SQL DataFrames
• Write and optimize SQL queries for data extraction, reconciliation and reporting
• Perform data quality checks, profiling and consistency validations
• Support existing data pipelines by troubleshooting failures and performing root cause analysis
• Work closely with data engineers, analysts, QA and DevOps teams in Agile delivery models
• Optimize performance of Spark jobs for efficiency and scalability
• Maintain technical documentation, workflows and runbooks
• Follow enterprise standards for coding, deployment and change management

Requirements

• 7–12 years of experience in Big Data / Data Engineering roles
• Strong hands-on experience with PySpark / Apache Spark
• Solid understanding of SQL and relational database concepts
• Experience working in Linux/UNIX environments
• Understanding of ETL concepts and large-scale data processing
• Strong analytical and debugging skills
• Experience supporting production data pipelines
• Exposure to Azure Databricks, ADF, Synapse or similar cloud data platforms
• Experience with Hadoop ecosystem (Hive, HDFS)
• Knowledge of orchestration tools (e.g., Airflow)
• Python scripting beyond Spark use cases
• Familiarity with Agile / DevOps delivery practices
• Domain exposure (e.g., Banking / BFSI, Analytics) is an advantage
• Strong problem-solving and ownership mindset
• Ability to work collaboratively in cross-functional teams
• Good communication and documentation skills
• Ability to adapt quickly in dynamic project environments

Benefits

• Comprehensive Medical Plan covering Medical, Dental, Vision
• Short Term and Long-Term Disability Coverage
• 401(k) Plan with Company match
• Life Insurance
• Vacation Time, Sick Leave, Paid Holidays
• Paid Paternity and Maternity Leave