Data Engineer

We're looking for a Data Engineer to help build and scale our data platform. You'll work closely with a small, focused data team and collaborate with Product, Analytics, and Engineering to turn business problems into reliable data solutions. This is a hands-on role where you'll get the opportunity to work across data pipelines, real-time systems, data modeling, and cloud infrastructure, while gradually taking ownership of larger parts of the platform.

Responsibilities:

• Build, maintain, and optimize data pipelines that power analytics and business-critical use cases.
• Work with the team to design and implement batch and real-time data workflows.
• Write clean, efficient, and well-tested SQL and code for data processing.
• Work with product, analytics, and engineering teams to understand requirements and translate them into data solutions.
• Contribute to data modeling and help build reliable, scalable datasets for downstream consumers.
• Monitor pipelines, troubleshoot issues, and proactively identify opportunities to improve reliability and performance.
• Follow and contribute to data quality, testing, and observability practices.
• Participate in technical discussions and contribute to architectural and design decisions.
• Identify recurring problems and technical debt, and work with the team to improve systems rather than just fixing symptoms.
• Document your work and share context with the team to make systems easier to understand and maintain.
• Take increasing ownership of data products and pipelines as you grow within the role.

Requirements:

• 1-4 years of experience in data engineering or a closely related role.
• Hands-on experience with cloud data platforms, preferably AWS (Glue, Redshift, Athena, EMR).
• Strong SQL skills and a good understanding of data modeling concepts.
• Experience building and maintaining ETL/ELT pipelines and working with batch or real-time data.
• Familiarity with tools such as Spark, Airflow, dbt, or similar data engineering technologies.
• Understanding of data quality, testing, monitoring, and pipeline observability.
• Experience with Python or another programming language commonly used for data engineering.
• Basic understanding of CI/CD and version control practices.
• Strong problem-solving skills and curiosity to understand why something needs to be built, not just what needs to be built.

Good to have:

• Experience working with real-time streaming technologies such as Kafka.
• Experience with large-scale data processing.
• Exposure to data warehouses such as Redshift, Snowflake, or BigQuery.
• Experience working in a fast-paced startup or consumer technology environment.