Data Engineer

We're seeking a motivated Data Engineer to join our growing team. You'll be responsible for building and maintaining data pipelines and ensuring our solutions have access to clean, reliable, and well-structured data. This is an excellent opportunity to learn and grow in a fast-paced environment where you'll work alongside other data engineers (incl. software developers), and product teams. You'll gain hands-on experience with modern data technologies.

Key Responsibilities

Data Pipeline Development

• Build and maintain ETL/ELT pipelines to ingest data from various sources (databases, APIs, files, third-party systems)

• Transform raw data into structured formats suitable for application use

• Implement data validation and quality checks throughout pipelines

• Schedule and monitor automated data workflows

• Debug and fix pipeline failures promptly

Data Integration & API Support

• Build integrations between different data systems and applications

• Create and maintain APIs for data access and retrieval

• Support agent tool integrations that require data access

• Work with external APIs to fetch and sync data

• Document data schemas, pipelines, and integration points

Data Quality & Monitoring

• Implement data quality checks and validation rules

• Monitor data pipeline health and set up alerts for failures

• Investigate and resolve data inconsistencies or anomalies

• Create data quality reports and dashboards

• Maintain data lineage and documentation

Collaboration & Support

• Work closely with other engineers to understand data requirements for agentic workflows

• Support product and engineering teams with data-related questions

• Participate in sprint planning and Agile ceremonies

• Contribute to technical discussions and code reviews

• Document processes, pipelines, and best practices

Required Qualifications

Education & Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering, or related field

• Experience with SQL and relational databases

• Basic understanding of data pipeline concepts and ETL processes

• Exposure to cloud platforms (AWS, Azure, or GCP)

Technical Skills

• Strong proficiency in Python for data processing and scripting

• Solid SQL skills - writing queries, joins, aggregations, and optimizations

• Experience with at least one relational database (PostgreSQL, MySQL, SQL Server)

• Understanding of data modeling concepts (normalization, star schema, etc.)

• Familiarity with version control using Git

• Basic understanding of Linux/Unix command line

• Knowledge of data formats (JSON, CSV, Parquet, etc.)

Preferred Skills

• Experience with Python data libraries: polars, pandas, numpy

• Familiarity with ETL/orchestration tools: Airflow, Prefect, Dagster, or similar

• Basic understanding of APIs and REST principles

• Knowledge of containerization (Docker)

• Understanding of data warehousing concepts

Soft Skills

• Eager learner - enthusiastic about learning new technologies and best practices

• Problem solver - logical approach to debugging and troubleshooting

• Detail-oriented - careful with data quality and accuracy

• Collaborative - works well in team environments and asks for help when needed

• Communicator - can explain technical concepts clearly

• Self-motivated - takes initiative and ownership of tasks

• Adaptable - comfortable with changing priorities in an agile environment

What You'll Work With

Programming Languages

• Python (primary) - polars, requests, SQLAlchemy (or other ORMs)

• SQL (extensive use across multiple databases)

• Understanding of Bash scripting for automation

• Understanding of containers (e.g. Docker)