Job Description – Lead Big Data Engineer

Job Title: Lead Big Data Engineer
Experience: 7–9 Years
Location: All EXL Locations (Hybrid)
 

About the Role

We are looking for a Lead Big Data Engineer with 7–9 years of experience in designing, developing, and optimizing large-scale data processing solutions. The ideal candidate will have strong expertise in Python, Apache Spark, Hadoop ecosystem, Hive, and SQL , with experience building scalable data pipelines and processing high-volume structured and unstructured data. The role requires close collaboration with cross-functional teams to deliver robust, high-performance data engineering solutions.

Key Responsibilities

• Design, build, and maintain scalable big data pipelines using Python and Apache Spark .
• Develop and optimize batch and distributed data processing applications on the Hadoop ecosystem .
• Build and manage data warehousing solutions using Hive and write efficient SQL queries for data analysis and transformation.
• Optimize Spark jobs for performance, scalability, and resource utilization.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver reliable solutions.
• Perform data ingestion, cleansing, transformation, and validation across multiple data sources.
• Troubleshoot production issues and ensure high availability and reliability of data platforms.
• Lead code reviews, mentor junior engineers, and drive engineering best practices.
• Ensure data quality, governance, security, and compliance standards are followed.
• Participate in Agile ceremonies and contribute to solution design and technical discussions.

Required Skills

• 7–9 years of experience in Big Data Engineering.
• Strong programming experience in Python .
• Hands-on expertise with Apache Spark for large-scale data processing.
• Experience working with the Hadoop ecosystem (HDFS, YARN, MapReduce).
• Strong knowledge of Hive for data warehousing and querying.
• Advanced SQL skills for data manipulation, optimization, and performance tuning.
• Experience building ETL/ELT pipelines for large datasets.
• Strong understanding of distributed computing concepts and data processing frameworks.
• Experience with version control systems such as Git.
• Excellent analytical, problem-solving, and debugging skills.

Preferred Skills

• Experience with workflow orchestration tools such as Airflow or Oozie.
• Exposure to cloud platforms (AWS, Azure, or GCP).
• Knowledge of Kafka or other streaming technologies.
• Familiarity with CI/CD practices and DevOps concepts.
• Experience working in Agile/Scrum environments.

Education

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.