Analytics Engineer

The is a hybrid opportunity with 4-days onsite in Suwanee. Candidates MUST be local to the Atlanta area. This role is not open to C2C, OPT, or any Visa consideration. No vendor support of any kind allowed. JOB DESCRIPTION Core Job Requirements • 5+ years of experience in analytics engineering, data engineering, or advanced business intelligence roles within a modern data stack environment • Advanced proficiency in SQL with demonstrated experience building performance, well-modeled analytical datasets • Hands-on experience with dbt for analytics-layer modeling, testing, and documentation • Experience working with cloud data warehouses, preferably Snowflake, including performance tuning and cost-aware design • Strong understanding of analytics engineering best practices, including: • Star and snowflake schemas • Incremental models • Fact / dimension separation • Medallion Architecture • Experience working in a CI/CD-driven analytics environment, including version control, code review, and deployment pipelines • Proven ability to partner closely with business stakeholders to translate requirements into trusted analytical assets • Bachelor’s degree in Analytics, Information Systems, Computer Science, Mathematics, Finance, or equivalent practical experience Sales Operations Domain Expertise (Required Emphasis) • Proven experience supporting Sales Operations, Revenue Operations, or Commercial Analytics functions • Strong knowledge of sales and revenue data domains, including: • Pipeline and funnel metrics • Bookings, billings, and revenue recognition concepts • Quota, attainment, and compensation-related metrics • Forecasting, actuals vs. targets, and variance analysis • Experience integrating and modeling data from CRM platforms (e.g., Salesforce or similar) • Ability to design sales performance and executive dashboards that support: • GTM leadership • Capacity planning • Territory and account analytics • Comfort working with imperfect or evolving operational data and establishing trust through modeling, validation, and documentation Commercial Real Estate / Data Center Experience (Strong Preference) • Experience working with commercial real estate, data center operations, or infrastructure?driven businesses preferred • Familiarity with real estate–specific concepts such as: • Building and location hierarchies • Lease, colocation, and contract structures • Capacity, utilization, and availability metrics • Experience modeling data across site, campus, region, and portfolio hierarchies • Ability to align sales analytics with physical asset constraints (e.g., capacity, power, occupancy) is a strong differentiator Technical & Platform Skills • Advanced SQL and data modeling expertise • dbt (models, tests, macros, docs, exposures) • Snowflake (query optimization, warehouse usage patterns, role-based access awareness) • Experience integrating data from SaaS systems using ELT tools (e.g., Fivetran, Stitch, etc.) • Familiarity with metadata management, data quality checks, and analytical lineage Professional & Communication Skills • Strong business acumen with the ability to frame data in commercial terms • Clear, concise communicator capable of working with: • Sales leadership • Data engineering and platform teams • Ability to write clear, durable documentation for models, metrics, and assumptions • High attention to detail with a strong bias toward accuracy, consistency, and auditability • Comfortable operating in a federated enterprise environment with multiple upstream systems