Data Engineer

We are looking for a skilled Data Engineer to design, build, and maintain the pipelines and models that power our analytics, reporting, and machine learning initiatives. You’ll be central to transforming raw data into reliable, actionable insights by integrating diverse sources into a unified data platform. This is a hands-on role where you’ll own the end-to-end data flow — from ingestion and transformation to modeling and optimization — ensuring that data across the company is high-quality, consistent, and scalable. Key Responsibilities

Design, develop, and maintain data ingestion, transformation, and modeling pipelines.

Build and optimize data models to support analytics, dashboards, and KPIs.

Deliver data models for use by ML Engineers, Data Analysts, and Data Scientists.

Ensure data quality, reliability, and governance across ingestion and transformation workflows.

Collaborate cross-functionally on initiatives requiring clean, well-structured data.

Continuously improve performance, scalability, and maintainability of data workflows.

Core Technologies

Fivetran – for automated, scalable data ingestion.

Snowflake – as our centralized, cloud-native data warehouse.

GraphQL – for flexible, application-agnostic data consumption.

Required Qualifications

4+ years of experience in data engineering, with strong pipeline and modeling expertise.

Deep knowledge of data warehousing and data modeling in cloud platforms (e.g., Snowflake).

Hands-on experience with Fivetran and GraphQL.

Strong skills in SQL and Python for data manipulation and pipeline development.

Familiarity with AWS and Google Cloud environments.

Understanding of data governance, schema evolution, and CI/CD practices.

Preferred Qualifications

Experience with Snowpark AI / Cortex or similar AI-enabled data platforms.

Exposure to Connector SDK for building custom connectors.

Knowledge of data security, replication, and failover strategies.

Experience working with educational data platforms or LMS systems.