AWS Lambda, Agile Programming Methodologies, Amazon Web Services (AWS), Business Intelligence, Centers for Disease Control and Prevention (CDC), Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Cross-Functional, Customer/Client Research, Data Analysis, Data Collection, Data Management, Data Quality, Data Warehousing, Database Extract Transform and Load (ETL), Dimensional Modeling, Engagement Marketing, Performance Management, Performance Tuning/Optimization, Python Programming/Scripting Language, Query Optimization, SQL (Structured Query Language), Scalable System Development, Sports, Use Cases
Location: Remote
Type: Long-Term Contract
Experience: 8+
Domain: Sports Analytics / Customer Data Platform
Job Summary We are looking for an AWS Data Engineer with strong hands-on experience in DBT, AWS data stack, and dimensional modeling. The role involves building scalable, cloud-native data platforms to support analytics, marketing, and fan engagement use cases.
Must-Have Skills - 5+ years of experience in Data Engineering / Analytics Engineering
- 3+ years of hands-on experience with DBT (models, macros, packages)
- Strong experience with AWS services: Glue, Lambda, Step Functions, MWAA (Airflow), Redshift
- Advanced SQL skills with performance tuning
- Strong experience in Data Warehousing & Dimensional Modeling
- Experience building ETL / ELT pipelines
- Hands-on experience with AWS CDK (IaC)
- Experience with CI/CD tools (CodePipeline, CodeCommit)
- Knowledge of Jinja templating (DBT)
- Understanding of Change Data Capture (CDC)
Key Responsibilities - Design and build scalable data pipelines using DBT, SQL, and AWS
- Develop and maintain data warehouse solutions (Redshift)
- Implement dimensional models for analytics and BI
- Optimize SQL queries and improve data performance
- Ensure data quality, governance, and reliability
- Build infrastructure using AWS CDK and CI/CD pipelines
- Collaborate with cross-functional teams and support Agile delivery
Nice to Have - Experience in Sports / Media / Customer Analytics
- Exposure to Customer Data Platforms (CDP)
- Experience with Python / PySpark