AWS Data Engineer

Inizio Partners Corp; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Inizio Partners Corp seeks an experienced Data Engineer to architect and implement a cloud-native data ecosystem supporting sports analytics and customer platforms. You will build scalable pipelines, warehousing solutions, and data assets powering analytics across digital products, fan engagement, and marketing domains.

You will collaborate with cross-functional teams, apply CI/CD and data governance best practices, and help optimize performance and reliability at scale.

Qualifications

• Bachelor's or Master's in a quantitative or technical field such as Statistics, Mathematics, Computer Science, Information Technology, Computer Engineering or equivalent.
• 5+ years of experience in data engineering and analytics on modern data platforms.
• 3+ years' extensive experience with DBT or similar data transformation tools, including building complex & maintainable DBT models and developing DBT packages/macros.
• Deep familiarity with dimensional modeling/data warehousing concepts and expertise in designing, implementing, operating, and extending enterprise dimensional models.
• Understand change data capture concepts.
• Experience working with AWS Services (Lambda, Step Functions, MWAA, Glue, Redshift).
• Hands-on experience with AWS CDK, CodeCommit, and CodePipeline for infrastructure automation and CI/CD.
• Python proficiency or general knowledge of Jinja templating in Python and/or PySpark.
• Agile experience and willingness to work with extended offshore teams and assist with design and code reviews with customer.
• A great teammate and self-starter, strong detail orientation is critical in this role.

Responsibilities

• Design and build robust, scalable data transformation pipelines using SQL, DBT, and Jinja templating
• Develop and maintain data architecture and standards for Data Integration and Data Warehousing projects using DBT and Amazon Redshift
• Collaborate with cross-functional teams to gather requirements and deliver dimensional data models that serve as a single source of truth
• Own the full stack of data modeling in DBT to empower analysts, data scientists, and BI engineers
• Enhance and maintain the analytics codebase, including DBT models, SQL scripts, and ERD documentation
• Ensure data quality, governance alignment, and operational readiness of data pipelines
• Apply software engineering best practices such as version control, CI/CD, and code reviews
• Optimize SQL queries for performance, scalability, and maintainability across large datasets
• Implement best practices for SQL performance tuning, including partitioning, clustering, and materialized views
• Build and manage infrastructure as code using AWS CDK for scalable and repeatable deployments. Integrate and automate deployment workflows using AWS CodeCommit, CodePipeline, and related DevOps tools
• Support Agile development processes and collaborate with offshore teams

Skills

Dimensional modeling

Data governance

Agile

Team collaboration

Education

Bachelor's or Master's in quantitative/technical field

Tools

DBT

SQL

Python

Jinja templating

AWS CDK

CodeCommit

CodePipeline

AWS services (Lambda, MWAA, Redshift)

Job description

We are seeking a seasoned Data Engineer to join our Sports Analytics & Engineering Practice. This role is pivotal in shaping and implementing our client's vision for a cutting-edge, cloud-native data ecosystem. You will architect and build scalable data infrastructure that transforms raw data into high-value assets, powering analytics across digital products, fan engagement, and marketing domains. Your work will directly contribute to the development of a world-class customer data platform.

Responsibilities:

• Design and build robust, scalable data transformation pipelines using SQL, DBT, and Jinja templating
• Develop and maintain data architecture and standards for Data Integration and Data Warehousing projects using DBT and Amazon Redshift
• Collaborate with cross-functional teams to gather requirements and deliver dimensional data models that serve as a single source of truth
• Own the full stack of data modeling in DBT to empower analysts, data scientists, and BI engineers
• Enhance and maintain the analytics codebase, including DBT models, SQL scripts, and ERD documentation
• Ensure data quality, governance alignment, and operational readiness of data pipelines
• Apply software engineering best practices such as version control, CI/CD, and code reviews
• Optimize SQL queries for performance, scalability, and maintainability across large datasets
• Implement best practices for SQL performance tuning, including partitioning, clustering, and materialized views
• Build and manage infrastructure as code using AWS CDK for scalable and repeatable deployments. Integrate and automate deployment workflows using AWS CodeCommit, CodePipeline, and related DevOps tools
• Support Agile development processes and collaborate with offshore teams

Required Qualifications:

• Bachelor's or Master's (preferred) degree in a quantitative or technical field such as Statistics, Mathematics, Computer Science, Information Technology, Computer Engineering or equivalent
• 5+ years of experience in data engineering and analytics on modern data platforms
• 3+ years' extensive experience with DBT or similar data transformation tools, including building complex & maintainable DBT models and developing DBT packages/macros
• Deep familiarity with dimensional modeling/data warehousing concepts and expertise in designing, implementing, operating, and extending enterprise dimensional models
• Understand change data capture concepts
• Experience working with AWS Services (Lambda, Step Functions, MWAA, Glue, Redshift)
• Hands-on experience with AWS CDK, CodeCommit, and CodePipeline for infrastructure automation and CI/CD
• Python proficiency or general knowledge of Jinja templating in Python and/or PySpark
• Agile experience and willingness to work with extended offshore teams and assist with design and code reviews with customer
• A great teammate and self-starter, strong detail orientation is critical in this role.