Data Analytics Engineer

Data Analytics Engineer to design, build, and scale the analytics layer that enables leaders across Marketing, Finance, Operations, Revenue Management, and Reservations to make data-driven decisions with confidence.

This role engineers governed data models, semantic layers, and high-performing BI assets on top of Snowflake, SQL Server (SSMS), and Oracle, delivered through Tableau and Power BI. The engineer will apply software engineering practices to analytics, version control, CI/CD, testing, documentation, ensuring consistency, trust, and automation across the BI ecosystem.

Key Responsibilities

Data Modeling & Analytics Engineering

• Develop and maintain analytics-ready data models and marts in Snowflake and SQL Server.
• Build and optimize semantic layers / governed KPI frameworks (dbt, metrics layers, semantic modeling).
• Write and optimize SQL (window functions, CTEs, partitioning, clustering) for high-performance reporting workloads.
• Apply data modeling best practices (star schema, snowflake schema, medallion/lakehouse).

BI Development & Enablement

• Build, optimize, and govern dashboards and reports in Tableau and Power BI for enterprise use.
• Translate ambiguous business requirements into scalable, reusable BI solutions.
• Automate recurring manual reporting tasks into robust pipelines and dashboards.
• Implement RLS/OLS, usage monitoring, and deployment pipelines for BI platforms.

Data Quality, Governance & Reliability

• Implement data quality testing and monitoring frameworks (dbt tests, Great Expectations, Soda).
• Apply governance standards for KPIs, metadata, lineage, and access controls.
• Document business logic, models, and BI workflows for reuse and auditability.
• Track SLAs/SLOs for key datasets and proactively address data issues before they impact users.

Collaboration & Continuous Improvement

• Partner with business stakeholders (Finance, Marketing, Ops, Revenue) to refine requirements into technical BI solutions.
• Collaborate with data engineers to ensure upstream pipelines support analytic use cases.
• Audit and modernize legacy BI assets for accuracy, reliability, and performance.
• Stay current on modern BI practices (semantic layers, augmented analytics, data catalogs, observability).

Qualifications

Required

• 3–6 years in a BI Engineer / Data Analytics Engineer role (or similar).
• Strong SQL development across Snowflake, Oracle, SQL Server.
• Hands-on BI development experience in Tableau (required) and Power BI (strongly preferred).
• Proven ability to design data models, semantic layers, and governed KPI frameworks.
• Experience applying data governance, validation, and testing practices.
• Familiarity with Git/GitHub workflows, CI/CD pipelines, and code reviews.
• Excellent communication skills for working directly with business leaders and technical teams.

Preferred

• Experience with dbt or other transformation frameworks.
• Familiarity with Azure Synapse Analytics or Microsoft Fabric Gen 2.
• Exposure to ETL/ELT orchestration (Airflow, SSIS, Azure Data Factory).
• Working knowledge of Python or R for automation or lightweight transformations.
• Experience with metadata/catalog tools (Alation, Collibra, Purview, DataHub).
• Domain experience in hospitality, travel, finance, or consumer industries