Senior Data Engineer - AWS

Location: New York

Think of TEKsystems Global Services (TGS) as the growth solution for enterprises today. We unleash growth through technology, strategy, design, execution and operations with a customer-first mindset for bold business leaders. We deliver cloud, data and customer experience solutions. Our partnerships with leading cloud, design and business intelligence platforms fuel our expertise. We value deep relationships, dedication to serving others and inclusion.

We drive positive outcomes for our people and our business, and we stay true to our commitments and act in harmony with our words. We exist to create significant opportunity for people to achieve fulfillment through career success. Ready to join us? Heres what the opportunity supported through our TGS Talent Acquisition Team requires:

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.

Essential Functions 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/SNSAmazon Redshift, RDS/Aurora, DynamoDBSnowflake 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

Mandatory Skills/

Competencies:

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/SNSAmazon Redshift, RDS/Aurora, DynamoDBAthena, Quicksight Strong working knowledge of Snowflake architecture, including

Virtual Warehouses Snowpipe / Copy Command / Dynamic Table…