Senior Analytics Engineer

Toters • Geraldine, AL

23h

About The Position

Toters is an on-demand e-commerce and delivery platform that operates a service enabling customers to get anything in their city with the highest level of convenience. At Toters, technology is central to all operations. Product teams work daily to create products that simplify customers' lives, while engineers continuously develop solutions to enhance process efficiency, ensuring fast and cost-effective delivery. This role is ideal for individuals interested in a high-growth startup environment and contributing to a team that may redefine online shopping in the Middle East.

As a Senior Analytics Engineer, you will serve as a vital link between Data Engineering and Data Analytics. In a fast-paced, high-volume transactional setting, the availability of clean, reliable, and scalable data is paramount. You will apply software engineering best practices to analytics workflows, taking responsibility for the data warehouse architecture, constructing robust data models, and designing ELT pipelines that empower analysts, data scientists, and business leaders to make high-impact decisions.

Requirements

• 4+ years of experience in Analytics Engineering, Data Engineering, or a highly technical Data Analytics role, ideally within a high-growth tech company, delivery platform, or multi-sided marketplace.
• Unmatched proficiency in writing complex, highly performant SQL.
• Extensive, hands-on experience building production-grade environments in dbt (including Jinja, macros, and incremental logic).
• Deep conceptual and practical understanding of modern columnar data warehouses (Snowflake, BigQuery, or Databricks) and architecture best practices.
• Fluent in Git workflows, command-line interfaces, and setting up CI/CD workflows for data deployments.
• Strong proficiency in Python for API integrations, custom transformations, or pipeline scripting.
• Demonstrated ability to translate complex operational logic (e.g., courier dispatch algorithms, funnel attribution, financial reconciliation) into elegant data architecture.

Nice To Haves

• Hands-on experience with modern data orchestration tools (Apache Airflow, Dagster, or Prefect).
• Experience managing event-tracking pipelines (Snowplow, Segment, Amplitude).
• Previous experience managing the semantic layer in BI platforms like Tableau.

Responsibilities

• Design, build, and maintain highly scalable and modular data models using dbt (data build tool) within a cloud data warehouse (e.g., BigQuery, Snowflake, or Databricks), transforming raw data into a reliable "single source of truth."
• Architect and optimize ELT pipelines to integrate complex, high-volume datasets across a 3-sided marketplace (app clickstreams, operational logistics, merchant catalogs, and financial transactions).
• Champion and enforce software engineering practices within the data team, including version control (Git), CI/CD pipelines, code reviews, and writing DRY (Don't Repeat Yourself) code.
• Implement rigorous automated testing, alerting, and anomaly detection to guarantee data integrity and build trust with downstream stakeholders.
• Design intuitive semantic layers and heavily documented data marts that empower Product Analysts and Business operators to independently explore data without writing complex SQL.
• Audit and optimize legacy queries, streamline warehouse compute resources, and ensure BI tools (Tableau) run with minimal latency.
• Elevate the technical baseline of the entire Data Analytics team by teaching advanced SQL, dbt modeling techniques, and performance-tuning strategies.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed