We are looking for aSenior Data Engineerto join a high-performing data engineering team at a leading general company operating at the intersection ofsports, technology, and digital commerce.

In this role, you will take ownership of the systems responsible foringesting, transforming, validating, and publishing dataacross a large-scale data ecosystem. You will work at the data ingestion boundary, where information from multiple internal and external sources enters the platform, ensuring it is accurate, reliable, and ready to power downstream products, analytics, and services.

You will be responsible for building and maintainingscalable data pipelines, solving complexidentity and entity-matching challenges, identifying and addressing data-quality issues, and improving the reliability and observability of data flows across the organization.

This is a highly hands-on engineering role that combinesAWS data engineering, Python, SQL, event-driven architectures, data quality, and identity resolution. You will work closely with engineering, product, analytics, and downstream platform teams to troubleshoot complex data challenges, improve existing systems, and build reliable solutions that support data-driven products at scale.

What You'll Do
•Own and evolve data ingestion pipelinesthat bring data from multiple external and internal sources into the platform, including ingestion, cleaning, curation, entity resolution, and event-driven publishing.
• Design, build, and maintainscalable batch and event-driven data workflowsusing Python, SQL, and AWS.
• Solve complexidentity resolution, entity matching, and deduplication challengesacross multiple data sources, ensuring reliable and consistent entity mappings.
• Build and maintaindata quality and validation frameworks,



including freshness monitoring, null-rate and consistency checks, and schema-drift detection.
• Monitor data at the ingestion boundary and proactively identify, troubleshoot, and resolve issues before they impact downstream products and services.
• Partner with engineering teams responsible forevent infrastructure and downstream identity servicesto trace data and events end-to-end.
• Collaborate withProduct, Assessments, Analytics, and Engineeringteams to understand how data is consumed downstream and ensure pipelines meet evolving product and business requirements.
• Work with AWS services such asGlue, Athena, S3, and DynamoDBto build and operate reliable, scalable data infrastructure.
• Automate infrastructure and pipeline changes usingInfrastructure as Code, primarily Terraform or AWS CDK.
• Participate inproduction incident response, quickly assessing impact, identifying root causes, and implementing effective remediation.
• Continuously improve thereliability, observability, scalability, and maintainabilityof data pipelines and platform infrastructure.

What You'll Bring
•5+ years of experiencebuilding and operating production-grade data pipelines and data infrastructure.
• Strong experience with bothbatch processing and event-driven architectures.
• Hands-on experience withAWS Glue, Athena, and S3-based data lakes,



including layered or medallion-style data transformations.
• Strong proficiency inPython and SQLfor data processing, transformation, and analysis.
• Experience solvingidentity resolution, entity matching, and deduplicationproblems, including exact and fuzzy matching approaches.
• Understanding ofdurable identifiers and identity-mapping strategies, including the challenges associated with maintaining consistent first-seen or locked mappings over time.
• Experience working withevent schemas and schema-registry-backed contracts, such as Protobuf, and an understanding of the impact of schema evolution on downstream consumers.
• Strongtroubleshooting and production incident-response skills, with the ability to assess impact, identify root causes, and drive issues through resolution.
• Ability to understand and debug code written in afunctional or concurrent programming language, such as Elixir.
• Strong communication and collaboration skills, with the ability to work effectively across engineering, product, analytics, and other technical teams.

Nice to Have
• Experience withElixir/Phoenixor otherBEAM-based concurrent processing frameworks.
• Experience withDynamoDB-backed identity, lookup, or matching services.
• Experience with theSnowflake ecosystem, including data modeling, Snowpipe, Streams, and Tasks.
• Experience working withsports data providers, licensed data providers, or other complex external data ecosystems.
• Experience implementingdata observability, including freshness and staleness alerts, null-rate monitoring, schema-drift detection, and data-quality dashboards.
• Experience managing infrastructure throughTerraform or AWS CDK.

📌 Data Engineer (Argentina)
🏢 Ryzlabs
📍 Argentina