Role Description We are seeking a highly skilled and motivated Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining robust data architectures and engineering data models and pipelines. This role will play a critical part in ensuring the integrity, scalability, and performance of our data processing and products. - Data Architecture: Design, develop, and implement scalable, secure, and efficient data solutions that meet the needs of the organization. - Data Modeling: Create and maintain logical and physical data models to support business intelligence, analytics, and reporting requirements. - Pipeline Engineering: Design, build, and optimize ETL (Extract, Transform, Load) processes and data pipelines to ensure smooth and efficient data flow from various sources. - Data Integration: Integrate diverse data sources, including APIs, databases, and third-party data, into a unified data platform. - Performance Optimization: Monitor and optimize the performance of data systems and pipelines to ensure low latency and high throughput. - Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to ensure the accuracy and reliability of data. - Collaboration: Partner closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs. - Documentation: Maintain comprehensive documentation of data architectures, models, and pipelines for ongoing maintenance and knowledge sharing. - Training: Train and collaborate with teammates effectively in data engineering best practices. - Technical Influence/Leadership: Recommend policy changes and establish department-wide procedures. Use extensive experience and knowledge to resolve complex problems. - Monitor and manage production environment to deliver data within defined SLAs. Qualifications - 5+ years of experience building, maintaining, and orchestrating scalable data pipelines. - 3+ years of experience as a data engineer developing or maintaining integration with software such as Airflow or any Python-based data pipeline codebase. - Experience applying a variety of integration patterns for different use cases. - Experience in backend software development to contribute to distributed computing development and data technologies. - Experience implementing data pipelines and improving the performance of ETL processes and related SQL queries. - Experience in data modeling for OLTP and OLAP applications. - Experience with Cloud platforms such as Amazon AWS. - Familiarity with workflow management tools (Airflow preferred). - Familiarity with cloud-based data warehouses (Amazon Redshift preferred). - Exceptional problem-solving and analytical skills. - Experience working with sensitive data (e.g., PHI / PII) & security best practices. - Familiarity with data governance practices and principles. Requirements - Proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL). - Proficiency in Analytical SQL and experience working with massive parallel processing (MPP) databases (e.g., Redshift, BigQuery, Snowflake). - Proficiency in programming languages such as Python, Java, or Scala. - Knowledge of data modeling techniques (3NF) and tools (e.g., ER/Studio, ERwin). - Software Engineering Mindset: Apply best practices to write elegant, maintainable code and understand automated testing concepts. - Familiarity with business intelligence tools and environments. - Familiarity with big data technologies (e.g., Lambda, Iceberg or Delta Lake, Spark, or Kafka). - Excellent communication and collaboration skills, both written and verbal. - Self-Directed: Leading projects and tasks effectively with cross-functional stakeholders with minimal guidance. Benefits - Competitive salary with generous annual cash bonus. - Equity grants. - Remote first work from home culture. - Flexible Time Off to help you rest, recharge, and connect with loved ones. - Generous parental leave. - Health, dental, and vision insurance (and above market employer contributions). - 401k retirement savings plan. - Lifestyle Spending Account (LSA). - Mental Health Support Solutions. - ...and more!