Rapidly growing SaaS company building a unified CRM and engagement platform for mortgage lenders, blending automation, analytics, and AI to drive productivity and customer success. We value innovation, scalable design, and the responsible use of data and AI to deliver actionable insights and exceptional customer experiences.

Role Overview :

Seeking a Senior Data Engineer to drive the design, deployment, and optimization of our modern data platform for a next-generation CRM product. As a technical and people leader, you will architect robust data pipelines, champion data quality, and collaborate closely with customers, QA, and DevOps to deliver scalable, AI-powered solutions. Join us to shape the future of data-driven customer engagement in a company that prizes innovation, transparency, and impact.

Key Responsibilities :

- Lead and mentor a 4-person data engineering team, fostering collaboration with QA and DevOps.

- Design, deploy, and optimize robust ETL/ELT pipelines using Apache Spark, Airflow, and Databricks.

- Architect and implement conceptual, logical, and physical data models based on evolving customer requirements.

- Oversee data warehousing solutions leveraging PostgreSQL, Redshift for analytics and reporting.

- Manage operational and OLTP data stores, ensuring appropriate use of MongoDB and relational databases.

- Engage directly with end users and customers to understand data challenges and translate needs into practical solutions.

- Establish and uphold data quality standards to ensure accuracy, completeness, and trust in all data products.

- Utilize AI and ML tools responsibly to enhance productivity, scalability, and decision-making within the data platform.

- Collaborate with DevOps for seamless deployment, monitoring, and infrastructure optimization.

- Communicate clearly on technical decisions, delivery status, risks, and trade-offs to both technical and business stakeholders.

Requirements :

1. Must have :

- Minimum of 5 years' experience in data engineering, with recent team leadership responsibilities.

- Bachelor's degree in Computer Science Engineering, or a related field.

- Proven expertise in ETL/ELT pipeline development using Apache Spark and Airflow.

- Strong skills in data modeling, relational (PostgreSQL) and NoSQL (MongoDB) databases.

- Demonstrated ability to mentor and coach technical teams.

- Excellent communication skills with both technical and non-technical stakeholders.

- Track record of delivering reliable, scalable, and high-quality data solutions.

2. Good to have :

- Experience with customer-facing data engineering projects.

- Understanding of business analysis and commercial priorities.

- Relevant certifications in data engineering or cloud platforms.

- Hands-on experience with modern data warehousing (Snowflake or Databricks).

3. Bonus :

- Experience in the mortgage or financial technology sector.

- Contributions to open-source data engineering projects.

Skills :

- Must have : ETL/ELT Pipeline Design, Apache Spark, Apache Airflow, Data Modeling, Data Warehousing, PostgreSQL, MongoDB, Apache Flink, Relational Database Design, Stream Processing, Data Quality Management.

- Good to have : Business Analysis, Customer Communication, Problem-solving, Team Leadership.

Benefits :

- Opportunity to lead a high-impact data engineering team.

- Work with modern data stack and cloud technologies.

- Collaborative, business-savvy, and innovative culture.

- Direct influence on product evolution and customer success.