Senior Data Engineer

About Us: Comfrt is one of the fastest-growing direct-to-consumer brands, dedicated to blending mental wellness, inclusivity, and elevated comfort into every piece we create. Our mission goes beyond clothing — we strive to build a community where everyone feels supported and seen. About the Job We are seeking a highly skilled and experienced Senior Data Engineer to join our growing data team. The ideal candidate will be responsible for designing, developing, and optimizing our data pipeline architecture to support our analytics, machine learning, and business intelligence initiatives. This role requires a strong background in big data technologies, cloud infrastructure, and a passion for building robust, scalable, and efficient data solutions. Data Architecture and Development Design, construct, install, test, and maintain highly scalable data management systems and processing pipelines using cloud-native services (e.g., AWS, GCP, Azure). Develop and optimize ETL/ELT processes to ingest, transform, and load data from various internal and external sources into our data warehouse/data lake. Implement data governance, security, and quality controls across all data pipelines. Ensure data architecture supports the needs of data scientists, analysts, and other business stakeholders. Analytics Engineering & BI Design and build Looker explores, views, and dashboards using LookML to serve self-service analytics across business domains including Revenue, CX, Operations, Logistics, and Finance. Develop and maintain LookML models following best practices: well-structured explores, reusable dimension/measure sets, PDTs, and derived tables. Partner with stakeholders to translate business questions into Looker explores and dashboards that drive operational decisions. Define and enforce reporting standards including MoM, YoY, and Forecast vs Budget vs Actual across all dashboards. Optimization and Performance Monitor, tune, and optimize data warehouse performance (e.g., Snowflake, BigQuery, Redshift). Troubleshoot and resolve complex data-related issues and performance bottlenecks in the data platform. Drive continuous improvement in data platform reliability, efficiency, and cost management. Collaboration and Mentorship Collaborate closely with data scientists, software engineers, and product managers to understand data requirements and deliver solutions. Define and enforce best practices for data engineering, including coding standards, documentation, and operational procedures. Mentor and guide junior data engineers, fostering a culture of technical excellence and continuous learning. Requirements Experience Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field. 5+ years of professional experience in data engineering, software engineering, or a related role focused on data infrastructure. Proven experience designing and building production-grade, highly reliable, and scalable data pipelines. Technical Skills Expert proficiency in SQL and at least one high-level programming language (e.g., Python, Scala, Java). Deep expertise with major cloud platforms (AWS, GCP, or Azure), specifically their data and storage services (e.g., S3, Google Cloud Storage, Azure Data Lake Storage). Solid experience with modern data warehousing solutions (e.g., Snowflake, Google BigQuery, Amazon Redshift). Experience with workflow orchestration tools (e.g., Apache Airflow, Dagster). Familiarity with distributed data processing frameworks (e.g., Apache Spark, Dask). Experience with version control systems (e.g., Git). Experience with AI tools (Claude, Vertex AI, Gemini). Hands-on experience with Looker — building and maintaining LookML models, explores, views, dimensions, measures, and derived tables in a production environment. Proficiency in LookML — including explores, joined views, PDTs (persistent derived tables), liquid templating, and Looker permissions/access controls. Strong understanding of Looker best practices: explore design, field naming conventions, caching strategies, and performance optimization. Preferred Qualifications Experience with stream processing technologies (e.g., Apache Kafka, Kinesis, Pub/Sub). Exposure to GenAI integration with development process. Knowledge of data modeling techniques (e.g., 3NF, Dimensional Modeling). Familiarity with machine learning pipelines (MLOps). Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation). Experience/Familiarity with D2C/E-Commerce Domain. Key Competencies Problem-Solving: Exceptional analytical and problem-solving skills with a high degree of attention to detail. Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical audiences. Ownership: A proactive mindset and a strong sense of ownership over the data platform and its integrity. Why Join Comfrt? Be part of a purpose-driven company that’s shaping the future of comfort and mental wellness. Work in a supportive, creative environment where your ideas and growth are valued. Enjoy Comfrt benefits such as generous paid time off, company-covered health insurance, 5% 401k match, and discounts on all Comfrt products. Join a passionate team making an impact on exciting projects, all while enjoying the flexibility and collaborative support of a fully remote environment. Comfrt is an equal opportunity employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. #J-18808-Ljbffr