Senior Data Engineer

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

Must have

• Minimum of 5 years'' experience in data engineering, with recent team leadership responsibilities
• Bachelors 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

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)

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
• Support for professional growth and AI skill development