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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - AWS - **Company:** TEKSYSTEMS INC. - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $109,700.0 - $164,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Business Analytics Applications, Data Analysis, Application Frameworks, ARM Architecture, Cloud Engineering, Continuous Integration, Data as a Services, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Sharing, DevOps, Amazon DynamoDB, JSON, Python (Programming Language), Machine Learning, Performance Tuning, Cloud Services, Azure Machine Learning, Software Deployment, SQL Databases, Extensible Markup Language (XML), Parquet, Data Ingestion, Snowflake, Data Strategy, Git, Servicebus, Semi-structured Data, Information Technology, Collibra, Deployment Automation, Data Analytics, AWS Data Analytics, Data Management, Tools for Reporting, Video Streaming, Amazon Simple Queue Service (SQS), Data Pipelines, Amazon Redshift, Databricks - **Published:** October 22, 2026 - **Apply:** https://dejobs.org/x/x/D0C33337EC6848008CF2174292307B13/job/ ## About the Role We are seeking a highly skilled Sr. Data Engineer with strong expertise in AWS Data & Analytics ecosystem, and Snowflake data platform to design and deliver modern, scalable data solutions. The ideal candidate should be a good team player with 6+ years of experience in data engineering with deep hands-on expertise in Amazon Web Services platform (S3, Glue, Lambda, Kinesis, Redshift, RDS/Aurora, Athena, Quicksight). Experience with AWS Sagemaker/Bedrock sevices is a definite plus. In addition, the candidate should have at least two end to end project experience developing Snowflake native data engineering solutions involving Snowpipe / Copy Command / Dynamic Table / Streams & Tasks This role requires expertise in designing, developing, and deploying secure, scalable, and high-performance cloud-native engineering and analytics solutions, close team collaboration with team lead/ architects, AI Engineers, Data Scientists, and Business Stakeholders to deliver impactful, data-driven solutions., * Bachelors or Masters degree in Computer Science, Engineering, or related field. * 6+ years of hands-on Data Engineering experience delivering enterprise-scale data platforms and analytics solutions * At least two end-to-end production grade implementation projects on AWS involving design, development, testing, and production deployment * At least two end-to-end implementation projects on Snowflake involving data ingestion, transformation, modeling, and optimization * Strong expertise in SQL, Python, and ETL/ELT development * Strong hands-on expertise in AWS data services, including: * Amazon S3 / Lake Formation * Glue, Lambda, EMR, Kinesis, Eventbridge, SQS/SNS * Amazon Redshift, RDS/Aurora, DynamoDB * Athena, Quicksight * Strong working knowledge of Snowflake architecture, including * Virtual Warehouses * Snowpipe / Copy Command / Dynamic Table * Streams & Tasks * Data Sharing * Performance Tuning * Security & Access Control * Expertise in data modeling (star/snowflake schemas, medallion architecture) * Experience building batch and near real-time data pipelines handling structured and semi-structured data (JSON, Parquet, CSV, XML) * Knowledge of CI/CD, Git, DevOps practices, and deployment automation * Experience implementing data quality, governance, security, and access controls in cloud platforms. * Strong problem-solving, communication, and stakeholder management skills * Excellent verbal and written communication skills. * Ability to participate in agile ceremonies (planning, retrospectives, backlog grooming) * Ability to work cross-functionally with product managers, business stakeholders, and engineering teams. * Passion for staying updated with the latest cloud and AI/ML technologies and ability to evaluate and adopt emerging tools and methodologies. Preferred Qualifications: * Experience with AWS Sagemaker / Bedrock and/or Snowflake Cortex AI/Cortex Code * AWS certifications such as: * AWS Data Engineer Associate * AWS Machine Learning Engineer Associate * Snowflake Certification such as: * SnowPro® Advanced: Data Engineer * SnowPro® Core Certification * Experience with Databricks * Familiarity with Streaming technologies (in AWS and/or Snowflake) * Exposure to data governance tools ## Description * Actively involves in requirement gathering workshops from customers, translating the functional requirements into technical solutions, and translating complex technical concepts into actionable insights for stakeholders under the guidance from an Architect or Lead Engineer * Actively participates in architectural discussions under guidance / supervision from Practice Architect / Team Lead to design and develop effective, efficient, reliable, secure, scalable, and cost-optimized data engineering solutions as per the overall data management strategy * Design and implement modern data platform architectures using AWS-native data services and/or Snowflake, including: * Amazon S3 / Lake Formation * Glue, Lambda, EMR, Kinesis, Eventbridge, SQS/SNS * Amazon Redshift, RDS/Aurora, DynamoDB * Snowflake Data Ingestion (different data formats) * Develop scalable data ingestion, transformation, and orchestration pipelines using AWS services * Design high-performance Lakehouse and Warehouse models following AWS Well Architected Framework guidelines * Design, implement, and optimize Snowflake-based cloud data platforms leveraging features such as Snowpipe, Streams, Tasks, Dynamic Tables, and Virtual Warehouses to deliver scalable, secure, and high-performance analytical solutions. * Develop enterprise-grade ELT frameworks and data integration solutions on Snowflake, ensuring adherence to data governance, performance optimization, cost management, and operational best practices * Build interactive and scalable semantic models and reports with Quicksight or other reporting tools * Implement CI/CD pipelines for data and analytics workloads * Ensure adherence to data governance, security, and compliance standards * Occasionally mentor or oversee junior engineers and drive best practices * Contribute to developing accelerator solutions or reusable frameworks