Data Engineer

About The Role

The role is responsible for designing, building, and optimizing the core data platform and infrastructure. This individual will develop robust, scalable data pipelines that process terabytes of data daily, enabling self-service analytics, machine learning workflows, and reliable executive reporting.

Working within a collaborative engineering team, the role bridges the gap between raw data production and downstream consumption. The engineer will focus on optimizing query performance, maintaining data quality frameworks, and ensuring high reliability across our hybrid-cloud data ecosystem.

Key Responsibilities

• Design, implement, and maintain highly scalable ELT/ETL pipelines using Python, SQL, and Apache Airflow.
• Build and optimize critical data models and schemas within Snowflake and dbt to support analytics and reporting use cases.
• Establish automated data quality checks, anomaly detection, and data lineage monitoring frameworks using Great Expectations or custom utilities.
• Collaborate with software engineers to integrate streaming and batch data sources from relational databases, APIs, and event streams like Kafka.
• Optimize data warehouse performance through efficient clustering, partitioning, and materialization strategies to manage compute costs.
• Manage infrastructure-as-code for data platforms using Terraform and maintain CI/CD pipelines for analytics code deployments.

What We Are Looking For

• 3-6 years of experience in data engineering, backend software engineering, or data infrastructure development.
• Expert-level SQL proficiency and strong programming skills in Python for data manipulation and scripting.
• Proven hands-on experience designing and operating modern data warehouses (e.g., Snowflake, BigQuery) and orchestration engines (e.g., Apache Airflow, Prefect).
• Solid understanding of data modeling techniques including dimensional modeling, star schemas, and Data Vault methodologies.
• Experience with cloud infrastructure services, preferably AWS, and version control workflows using Git.
• Bonus: Experience with dbt, Apache Spark, real-time streaming tools (Kafka/Kinesis), or infrastructure management with Terraform.