Senior Data Engineer

Scientific Games

Senior Data Engineer building and modernizing lottery data platform. Designing reliable data pipelines for analytics and reporting in a dynamic gaming environment.

Posted 6/13/2026full-timeAlpharetta • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AWSCloudETLSQL

About the role

Key responsibilities & impact

Design, build, and operate reliable data pipelines that move lottery data from operational systems into warehouse and analytics environments.
Improve ingestion, transformation, modeling, orchestration, observability, data quality, lineage, and access patterns.
Help define and implement data contracts covering schema, quality, timeliness, lineage, storage, access, and customer or jurisdiction constraints.
Build repeatable onboarding patterns for new jurisdictions, games, data sources, and reporting needs.
Partner with DBA, IT, product, application engineering, analytics, BI, and data science teams so source data is usable, trusted, and well-understood.
Reduce KTLO work through automation, better monitoring, resilient pipeline design, infrastructure as code, and platform simplification.
Troubleshoot production data issues and help create durable fixes rather than recurring manual workarounds.
Support the transition from legacy approaches to a more scalable cloud- and AI-ready data architecture while protecting business continuity.
Mentor other engineers through design reviews, code reviews, documentation, pairing, and clear technical standards.

Requirements

What you’ll need

5-7+ years of Data Engineering, Data Platform, or Data Warehousing experience
Extensive SQL and data modeling skills, including experience with analytical, reporting, and operational data use cases.
Strong background working in AWS or similar cloud environments
Experience with batch and streaming ingestion, ETL / ELT, orchestration, transformation frameworks, and data quality controls.
Experience working with data contracts, schema evolution, lineage, observability, access controls, and service-level expectations.
Experience improving legacy data platforms while maintaining production continuity.
Experience troubleshooting complex production data issues and turning recurring problems into durable fixes.
Experience with cloud data platforms, distributed processing, infrastructure as code, and modern data engineering practices.
Clear written and verbal communication; able to explain data behavior, tradeoffs, and risks to technical and non-technical partners.

Benefits

Comp & perks

Professional development opportunities
Flexible working arrangements

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringdata warehousingSQLdata modelingETLELTdata quality controlsinfrastructure as codecloud data platformsdistributed processing

Soft Skills

clear written communicationclear verbal communicationmentoringtroubleshootingcollaboration