Senior Data Engineer

LTIMindtree is seeking a Data Engineer to design, build, and optimize scalable data pipelines. The role focuses on reliable, efficient data processing for business intelligence and analytics, using Spark and cloud data platforms.

Responsibilities:

• Data Pipeline Development Maintenance Design build and maintain highly scalable and efficient ETLELT data pipelines utilizing PySpark and Spark SQL for complex data transformations
• Cloud Data Infrastructure Management Deploy manage and scale critical data infrastructure components on leading cloud platforms such as Amazon Web Services AWS eg EMR Glue Microsoft Azure eg Databricks Synapse or Google Cloud Platform GCP
• Data Warehousing Storage Optimization Strategically manage data layout partitioning and indexing within Apache Hive and various cloud data lake solutions to optimize performance and accessibility
• Performance Tuning Optimization Proactively identify and resolve performance bottlenecks in Spark jobs leveraging Spark UI for indepth analysis effectively managing data skewness and optimizing memory utilization
• Diverse Data Integration Develop robust solutions for ingesting highvolume and diverse datasets from both structured relational databases and unstructured flat files into our data ecosystem
• Automated Workflow Orchestration Implement and manage automated data workflows using industrystandard scheduling tools like Apache Airflow or platformnative schedulers ensuring timely and reliable data delivery
• Strategic Collaboration Partner closely with data scientists business analysts and crossfunctional enterprise teams to translate complex business requirements into technically sound and efficient data solutions

Requirements:

• Demonstrated high proficiency in Apache Spark architecture including a deep understanding of drivers executors and Directed Acyclic Graphs DAGs
• Exceptional coding skills in Python and extensive experience with the PySpark API for developing intricate data transformations and processing logic
• Strong command of HiveQL and ANSI SQL coupled with expertise in data partitioning techniques and effective schema definition
• Indepth understanding and practical experience with optimized big data storage file formats such as Parquet ORC and Avro
• Handson development experience utilizing cloudnative big data utilities eg AWS EMR Azure Databricks within major cloud platforms
• Solid foundation in Dimensional Data Modeling including Star and Snowflake schemas and practical experience with Data Lakes concepts and implementation
• Apache Spark
• Python
• Experience with Continuous IntegrationContinuous Deployment CICD practices and automation tools like Git Jenkins or Ansible
• Exposure to and experience with NoSQL databases such as HBase Cassandra or MongoDB
• Relevant professional cloud certifications eg AWS Certified Data Engineer Microsoft Certified Azure Data Engineer Associate are highly valued