Senior Data Engineer

We are seeking an experienced and visionary Senior Data Engineer to lead the design, architecture, and population of our new BI data warehouse. This role is highly cross-functional and critical to Incident IQ's next phase of growth. You will be responsible for aggregating complex data streams from our core SaaS platform (SQL, MongoDB) and third-party systems (Salesforce, Gainsight, etc.) into a centralized data warehouse/lake.

In this role, you will empower the entire company by unlocking internal reports and actionable insights. Furthermore, you will play a pivotal role in productizing this data by collaborating with product teams to build a scalable, customer-facing analytics version embedded within our platform.

• →Data Warehouse Architecture: Design, implement, and scale a modern BI data warehouse/data lake from the ground up, tailored to support both internal business analytics and external customer-facing reporting.
• →Data Pipeline Engineering: Build and maintain robust, automated ETL/ELT pipelines to extract and aggregate data from diverse sources including our SaaS platform databases (SQL, MongoDB), Salesforce, Gainsight, and other external APIs.
• →Customer-Facing Analytics: Collaborate with Product and Engineering teams to design the underlying data architecture for embedded, customer-facing analytics within the Incident IQ platform.
• →Data Quality & Governance: Establish and enforce data governance, quality checks, and performance optimization practices to ensure high data integrity and rapid query response times.

• Experience: Minimum of 5-7 years of professional experience in Data Engineering, BI Engineering, Analytics Engineering, or Data Architecture, specifically within a high-growth SaaS environment.
• Data Warehousing: Deep expertise in modern cloud data warehousing solutions (e.g., Snowflake, Databricks, Azure Synapse, or AWS Redshift) and data lake architectures.
• Pipeline Development: Proven experience building complex ETL/ELT pipelines using tools like dbt, Apache Airflow, Azure Data Factory, or similar orchestration frameworks.
• Database Mastery: Advanced proficiency in complex SQL, query tuning, and working with both relational (SQL Server, PostgreSQL) and NoSQL (MongoDB) databases.
• SaaS Integrations: Hands-on experience extracting and integrating data from enterprise GTM tools such as Salesforce, Gainsight, Marketo, or similar platforms.
• Programming: Proficiency in languages such as Python, Scala, or C# for data manipulation and automation.

• Strategic Builder: You don't just write scripts; you think holistically about how data architecture drives business outcomes and product differentiation.
• Cross-Functional Communicator: You can translate complex technical data models into plain business language for stakeholders, and vice versa.
• Autonomous Ownership: You thrive in environments where you can take a high-level goal, determine the technical path, and execute with minimal hand-holding.
• Inquisitive Problem Solver: You are naturally curious about how the business operates and how data can be used to uncover hidden efficiencies.
• Collaborative Team Player: Focused on the success of the platform and the company over personal credit.