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) MEDLYTIX