Data Engineer II

Versant•Orlando, FL

1d•Remote

About The Position

As a Data Engineer II on the Data Services team, you will build and operate the pipelines and data products that power GolfNow and Versant’s sports technology organization. Working within a modern AWS-based lakehouse, you will own production data systems and deliver trusted data used by analytics, product teams, and emerging AI applications. This is a hands-on engineering role with meaningful ownership. You will design solutions, operate them in production, solve problems at their source, and contribute to technical decisions as the platform evolves. Reliable, timely data helps GolfNow understand its customers, operate its business, and improve its products. You will help modernize workloads that still rely on legacy on-premises SQL Server infrastructure, building dependable pipelines and data products on AWS that teams can trust. This is a full-time, remote U.S. position with opportunities for in-person collaboration approximately 10% of the time.

Requirements

Hands-on experience building, deploying, and supporting cloud-based data pipelines, ideally using AWS technologies such as Glue, Lambda, Step Functions, Redshift, or comparable services.
Strong SQL and Python skills, including experience with ETL/ELT workflows using structured and semi-structured data.
Working knowledge of data modeling, warehousing, orchestration, and modern data engineering practices, with familiarity with technologies such as Airflow and Terraform.
Experience improving the performance, reliability, and resource utilization of production data systems, with a practical approach to troubleshooting and root-cause resolution.
Sound judgment when solving ambiguous problems independently, including understanding upstream and downstream dependencies and knowing when to involve others.
Clear communication skills and the ability to influence technical discussions and collaborate effectively across engineering, analytics, product, data science, and business teams.

Nice To Haves

Experience with dbt, Apache Iceberg, change data capture, or data products supporting LLMs or AI agents.
Exposure to SSIS, SSRS, PowerShell, or migrations from legacy SQL Server environments.
Familiarity with Tableau, Power BI, or QuickSight.
Experience working in an Agile engineering environment using tools such as Jira and Confluence.

Responsibilities

Design, build, and maintain scalable data pipelines and models within an AWS-based medallion lakehouse using technologies such as Amazon S3, Apache Iceberg, dbt, Amazon Redshift, and Airflow or Amazon MWAA.
Own production data services and improve reliability through monitoring, automated testing, resilient design, observability, deployment practices, and disaster recovery.
Build reusable components and automation that simplify dataset onboarding while applying sound practices for governance, lineage, schema evolution, security, and least-privilege access.
Develop trusted data products for reporting, analytics, APIs, and AI-powered applications, including data structures suitable for text-to-SQL and LLM-based use cases.
Support the migration of pipelines and reporting workloads from legacy SQL Server, SSIS, and SSRS environments, validating outputs and downstream dependencies before cutover.
Partner with engineering, product, analytics, and data science teams to solve business and technical problems.
Lead technical discussions and medium-sized cross-functional initiatives within your area of ownership, and support junior engineers through code reviews and guidance.