Data Analytics Engineer, Perchwell

• The ideal candidate will have a strong technical foundation, exceptional problem-solving skills, and experience in modern data stack technologies
• 5-10 years of work experience in data analytics, data engineering, or a similar role
• SQL: Advanced proficiency in SQL for querying, transforming, and optimizing large datasets
• Data Warehousing: Strong experience with Amazon Redshift or other cloud data warehouses (Snowflake, BigQuery, etc.)
• ETL/ELT Tools: Expertise with dbt to build modular, testable, and reusable transformation logic
• Programming: Proficiency in Python for scripting, automation, and working with APIs
• Workflow Orchestration: Experience with Airflow or similar orchestration tools to manage workflows
• CI/CD: Experience with CI/CD pipelines for version control, testing, and deployment of analytics code
• Data Modeling: Knowledge of data modeling best practices and the ability to design star/snowflake schemas
• Data Quality: Experience with tools, frameworks, or processes for data validation, testing, and reconciliation
• LLM & AI Knowledge: Exposure to Large Language Models (LLMs) and experience using them to support analytics, such as enabling natural language query interfaces
• Analytical Mindset: Strong problem-solving and critical-thinking skills
• Communication: Ability to communicate complex technical concepts to non-technical stakeholders
• Detail-Oriented: Precision in handling large datasets and ensuring data integrity
• Collaboration: A team player who thrives in cross-functional environments

Desirable

• We are seeking a motivated and experienced Data Analytics Engineer to join Perchwell’s growing data team
• This role will be pivotal in developing and maintaining scalable data pipelines, transforming raw data into usable formats, and enabling self-service analytics across the organization
• You will collaborate closely with data engineers, data analysts, and product managers to deliver high-quality, timely data solutions
• Data Pipeline Development: Design, build, and maintain ETL/ELT pipelines to process large volumes of structured and unstructured data
• Data Transformation: Use tools like dbt to transform raw data into clean, reusable data models that support self-service analytics
• Data Integration: Integrate data from multiple sources, ensuring data accuracy, quality, and consistency across platforms
• Data Governance: Ensure adherence to data quality and security standards, and support the implementation of data governance policies
• Automation & Orchestration: Utilize Airflow to schedule and monitor workflows, ensuring timely delivery of data
• CI/CD & Version Control: Implement CI/CD processes for analytics code, enabling rapid development, testing, and deployment
• Collaboration & Support: Work closely with cross-functional teams (Data Analysts, Data Scientists, Product Managers) to deliver data products that meet business needs
• Innovation: Stay up-to-date on the latest advancements in data engineering, large language models, and AI-driven analytics to drive innovation in Perchwell’s data strategy