Senior Data Engineer

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Company Overview

A growing technology company is developing AI-powered solutions designed to improve essential industries, including housing and healthcare. By integrating AI agents into existing workflows, the organization helps reduce manual work, improve accessibility, lower operational costs, and create better experiences for customers and end users.

In housing, its technology supports processes such as apartment tours, lease signing, maintenance requests, and communication between renters and property teams. In healthcare, its solutions help streamline appointment scheduling, patient intake, and communication between patients and providers.

The organization has secured significant investment to accelerate the development and expansion of its AI-powered solutions across these essential services.

As a Senior Data Engineer, the successful candidate will be a key member of the Engineering team, helping establish data as a strategic business asset. The role will involve working closely with product, operations, analytics, and other cross-functional teams to build data infrastructure that supports decision-making, product development, operational optimization, and customer-facing reporting.

The Senior Data Engineer will own core data pipelines and play a central role in designing, implementing, and maintaining data infrastructure and ETL processes. The position will also help ensure that engineering processes generate meaningful, high-quality data that is stored and processed efficiently.

Key Responsibilities

• Own the design, implementation, maintenance, and optimization of data pipelines and infrastructure.
• Build and maintain high-quality, large-scale data pipelines capable of processing significant volumes of data.
• Optimize data flow and collection processes to support cross-functional teams.
• Design core data objects and models used across the organization.
• Develop and maintain ETL processes for reliable and scalable data integration.
• Implement data quality checks and monitoring systems to maintain reliable datasets.
• Ensure engineering processes produce meaningful and accurately structured data.
• Optimize data storage and processing for performance and scalability.
• Develop client-facing reporting solutions that provide actionable insights.
• Create metrics datasets and dashboards to support data-driven decision-making.
• Collaborate with product, operations, analytics, and engineering teams to improve data quality and usability.
• Support the development of data infrastructure that powers internal strategy and customer-facing products.
• Establish and maintain development workflows and engineering best practices for data systems.
• Continuously identify opportunities to improve data processes, reliability, and efficiency.

Required Qualifications

• 4+ years of professional experience in data engineering.
• Strong programming proficiency in Python.
• Experience working with PostgreSQL or other relational databases.
• Proven experience in data modeling and database design.
• Hands-on experience designing, implementing, and maintaining ETL pipelines.
• Knowledge of data warehousing solutions, particularly Snowflake.
• Understanding of software development workflows and engineering best practices.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.
• Ability to work independently as well as effectively within a team.
• Strong organizational and time management skills.
• Adaptability and willingness to learn and work with new technologies.
• Commitment to maintaining high standards of data quality.

Preferred Qualifications

• Experience with data quality management and monitoring tools.
• Familiarity with AWS services.
• Familiarity with data visualization techniques and tools.
• Knowledge of machine learning pipelines and related tools.
• Experience with real-time data streaming platforms.
• Familiarity with dbt and Airflow.
• Experience working with scalable data infrastructure and analytics environments.

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