Key Responsibilities Design, develop, and support enterprise-scale data engineering solutions and scalable data pipelines Build and optimize large-scale data processing solutions using SQL, Python, PySpark, and Spark Develop and maintain modern data platform solutions using Snowflake, dbt, Kafka, Airflow, Iceberg, and Lakehouse architectures Design and implement cloud-native data solutions using AWS services such as EMR, Glue, Athena, Lambda, DynamoDB, EC2, IAM, CloudFormation, and CloudWatch Apply data architecture and modeling principles, including dimensional modeling, Data Vault, data warehousing, data governance, and master data management Design and implement data streaming and distributed data processing solutions Evaluate technical approaches and clearly communicate architecture decisions, implementation strategies, challenges, and outcomes Lead technical initiatives and collaborate with engineering teams to deliver scalable data solutions Gather business requirements and translate complex business needs into technical designs and solutions Collaborate with business stakeholders and technical teams throughout the development lifecycle Apply AI-assisted development tools, automation frameworks, and emerging technologies to improve engineering productivity, software quality, and delivery Continuously evaluate and adopt modern engineering practices and technologies that improve data platform capabilities Support CI/CD and DevOps practices for data engineering solutions Troubleshoot performance, reliability, and data quality issues across data pipelines and platforms Required Qualifications 5+ years of experience Good to Have Good to Have AWS Solutions Architect AWS Developer AWS Data Analytics Skills SQL Python PySpark AWS Cloud Services Snowflake dbt Kafka Airflow Iceberg And Lakehouse Architectures Data Pipeline Development Data Streaming And Distributed Data Processing CI/CD Pipelines Bash/Shell Scripting Relational, NoSQL, And Graph Databases Networking, Virtualization, And Distributed Systems Data Architecture And Modeling Technical Leadership Requirements Gathering Stakeholder Management AI-Assisted Development Troubleshooting And Performance Tuning DevOps Practices Linux Administration And Scripting Agile Delivery Distributed Team Collaboration Schedule Start date: 2026-10-07