Analytics Engineer

Analytics Engineer (Remote – Full-Time, Contract)

Location: Remote – Dominican Republic Compensation: $3,000 USD/month + discretionary bonus

Reports To: Director of Financial Reporting and Analysis

Position Overview

We are seeking a highly technical and business-minded Senior Analytics Engineer to join our finance team remotely from the Dominican Republic.

This role will play a key part in designing and maintaining our analytics infrastructure, including our data warehouse, semantic layer, and emerging AI-driven data access tooling (MCP servers). The Senior Analytics Engineer will translate raw operational and financial data into trusted, governed, and query-able datasets that power financial reporting, self-service analytics, and AI agents across the organization.

The ideal candidate will be fluent in English, hold a Bachelor's or Master's degree in a quantitative field, have deep expertise in SQL and modern data warehouse platforms, and be capable of building scalable data models that enable both human and AI consumers to make confident, data-driven decisions.

Key Responsibilities

• Design, build, and maintain data models and transformation pipelines within the data warehouse (e.g., Snowflake, BigQuery, Redshift, or Databricks).
• Develop and own the semantic layer, defining business metrics, dimensions, and entities that ensure consistent definitions across financial reports, dashboards, and AI applications.
• Build and maintain MCP (Model Context Protocol) servers that expose governed datasets, metrics, and tools to LLM-based agents and internal AI assistants.
• Write performant, well-documented SQL to support financial reporting, ad-hoc analysis, and downstream data products.
• Partner with Finance, FP&A, Operations, and Product teams to translate business questions into reliable data assets and self-service dashboards.
• Support the Financial Reporting and Analysis team with data infrastructure for consolidations, variance analysis, lender reporting, and cash flow forecasting.
• Establish data quality, testing, and observability standards across pipelines and semantic models.
• Document data lineage, metric definitions, and access patterns to support governance, audits, and onboarding.
• Collaborate with engineering on ingestion, schema evolution, and warehouse performance tuning.
• Support analytics enablement: train stakeholders on querying the warehouse, using the semantic layer, and interacting with AI-powered data tools.
• Participate in ad-hoc analytics projects and proofs-of-concept involving emerging AI/data tooling.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, Economics, Finance, or a related quantitative field (preferred).
• 5+ years of experience in analytics engineering, data engineering, or business intelligence, ideally supporting a finance or FP&A function.
• Expert-level SQL skills, including window functions, CTEs, performance tuning, and complex joins across large datasets (required).
• Hands-on experience with at least one modern cloud data warehouse — Snowflake, BigQuery, Redshift, or Databricks (required).
• Experience designing and maintaining a semantic layer using tools such as dbt Semantic Layer, Cube, LookML, AtScale, or equivalent (required).
• Working knowledge of MCP (Model Context Protocol) servers, or demonstrated experience exposing data and tools to LLM-based agents via APIs, function calling, or similar interfaces (strongly preferred).
• Strong understanding of dimensional modeling, ELT patterns, and data warehouse best practices.
• Familiarity with financial data structures (general ledger, chart of accounts, consolidations) is a plus.
• Experience with dbt or a comparable transformation framework.
• Proficiency with at least one BI tool (Looker, Power BI, Tableau, Mode, or similar).
• Familiarity with Python for data manipulation, scripting, or lightweight pipeline work is a plus.
• Fluent English (written and spoken) required for communication with U.S.-based teams.
• Excellent analytical, organizational, and problem-solving skills with strong attention to detail.

Ideal Candidate Profile

• Proactive, self-motivated, and highly accountable.
• Able to work remotely and independently while meeting deadlines.
• Strong communication skills and ability to explain technical concepts to non-technical stakeholders, including Finance leadership.
• Curious about emerging AI tooling and how LLMs are reshaping how organizations consume data.
• Bias toward building reusable, governed data assets over one-off reports.