Senior Data Engineer

Senior Data Engineer Overview:

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.

Senior Data Engineer Responsibilities: 

• 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.

Senior Data Engineer Requirements:

• 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.

Senior Data Engineer Personality & Soft Skills:

• 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.