Data Engineer

We are seeking a highly skilled Senior Data Engineer to design and implement scalable, high-performance data solutions. This role will serve as the bridge between business requirements and technical implementation translating strategic data needs into detailed design documents and data models that enable analytics, reporting, and business insights., * Design, develop, configure, test, and document scalable data solutions to meet business and technology requirements

• Analyze enduser, business, and technical needs and translate them into effective data and technology solutions
• Build, maintain, and optimize ETL/ELT data pipelines using AWS services, Python, SQL, and shell scripting
• Develop and sustain AWS-based data ingestion and data lake architectures using services such as S3, Glue, Redshift, Athena, Lambda, EMR, and RDS
• Evaluate existing data platforms and perform gap analysis to recommend performance and scalability improvements
• Collaborate with business analysts, data scientists, architects, SAP functional teams, and other stakeholders to resolve data-related issues
• Ensure solutions meet security, quality assurance, and compliance standards
• Monitor, troubleshoot, and support production data pipelines; identify root causes and implement short- and long-term fixes
• Support deployment of new data solutions, enhancements, upgrades, and fixes to production environments
• Participate in on-call rotations and incident response for mission-critical data systems
• Follow standard change management, release, and version control processes to ensure production readiness
• Document technical designs, data flows, system processes, and operational procedures

• Bachelor s degree with 4+ years of relevant experience
• 6+ years of experience in AWS data services (S3, Glue, Redshift, Athena, Lambda, EMR, RDS)
• 6+ years of experience in ETL/ELT development using Python, SQL, and shell scripting
• Proven expertise in dimensional modeling (Star and Snowflake schemas).
• Understanding of data modelling principles and techniques.
• Knowledge of data security best practices and compliance requirements.
• Experience with data lake architectures and integration with Redshift (e.g., S3, Lake Formation).
• Data lake integration with reporting tools such as Power BI
• Production support, monitoring, and troubleshooting of data pipelines
• Strong analytical, problem-solving, and communication skills
• AWS certification preferred.