We are seeking a highly motivated Analytics Engineer to join our dynamic data team. This role focuses on transforming raw data into actionable insights, ensuring data integrity, and optimizing data infrastructure. The ideal candidate will have hands-on experience with modern analytics tools like Airbyte, Fivetran, dbt, Snowflake, and Airflow.

Key Responsibilities:

Data Integration & ETL:

Design, implement, and manage ETL pipelines using Airbyte and Fivetran.
Maintain and optimize existing workflows for improved performance and scalability.

Data Modeling & Transformation:

Develop and maintain data models using dbt/dbt Cloud.
Transform raw data into structured, high-quality datasets that meet business needs.
Implement data quality checks to ensure consistency and integrity.

Data Warehousing:

Manage and optimize Snowflake or Redshift data warehouses for performance, storage, and security.
Implement best practices for partitioning, clustering, and indexing.

Collaboration & Communication:

Work closely with data analysts, data scientists, and business stakeholders to understand data requirements.
Communicate complex technical concepts clearly to non-technical stakeholders.

Continuous Improvement:

Stay updated on developments in data engineering and analytics tools.
Identify and implement process improvements, automation, and pipeline optimization.

Required Qualifications:

Bachelor's degree in Computer Science, Data Science, Information Systems, or related field.
3–5 years of experience in data engineering or analytics engineering.
Hands-on experience with ETL tools such as Airbyte and Fivetran.
Strong experience with dbt for data modeling and transformation.
Experience working with Snowflake or similar cloud data warehouses.
Proficiency in SQL; ability to write complex queries for data extraction and manipulation.
Familiarity with Python or other data engineering programming languages.
Knowledge of AWS and DevOps is a plus.

Analytics Engineer II