About Us
At True Path Leads, we're building the next generation of performance marketing infrastructure. Our proprietary lead management platform operates at scale, processing millions of pings and leads in real time. We are expanding rapidly and looking for a highly capable Senior Backend Engineer to help design, build, and scale our core lead processing engine and supporting services.

Tech Stack
Apache Kafka · Apache Airflow · SQL · NoSQL · ETL/ELT · Data Pipelines · Real-Time Data Processing · Batch Processing · Data Modeling · Distributed Systems · CI/CD · Infrastructure as Code (IaC) · Data Warehousing · Data Quality · Data Integration

What We're Looking For

We are looking for an experienced Senior Data Engineer to design, build, and maintain scalable data infrastructure supporting analytics, reporting, machine learning, and business operations.
The ideal candidate has strong experience with data pipelines, ETL/ELT processes, distributed systems, and database optimization, with a focus on reliability, performance, and scalability.

Responsibilities

Design, develop, and maintain scalable batch and real-time data pipelines.
Build and optimize ETL/ELT workflows for data ingestion, transformation, and delivery.
Develop and maintain data architectures supporting analytics, BI, and machine learning.
Implement and maintain streaming data pipelines using technologies such as Kafka and orchestration tools such as Airflow.
Design and optimize data models, schemas, and storage solutions across SQL, NoSQL, and analytical databases.
Ensure data quality through validation, deduplication, normalization, and reconciliation.
Optimize data pipelines for performance, scalability, latency, and cost efficiency.
Implement monitoring, logging, alerting, and fault-tolerance mechanisms.
Troubleshoot production issues involving databases, pipelines, and distributed systems.
Maintain data contracts, schema compatibility, data lineage, and documentation.
Implement data security best practices, including access controls, encryption, and PII protection.
Collaborate with engineering, analytics, product, and ML teams to deliver reliable data solutions.
Automate infrastructure deployment and maintenance using CI/CD and Infrastructure as Code.
Participate in architectural decisions and continuously improve data platform reliability and maintainability.

Requirements

Strong commercial experience in Data Engineering.
Hands-on experience designing and maintaining scalable data pipelines.
Strong knowledge of ETL/ELT processes and data integration.
Experience with batch and real-time data processing.
Experience with Kafka, Airflow, or similar technologies.
Strong understanding of relational, NoSQL, and analytical databases.
Experience with data modeling, schema design, and database performance optimization.
Understanding of distributed systems, fault tolerance, and high-availability architectures.
Experience implementing data quality checks, monitoring, and observability.
Familiarity with CI/CD practices and Infrastructure as Code.
Knowledge of data security, access management, and sensitive data protection.
Strong troubleshooting, analytical, and problem-solving skills.
Ability to collaborate effectively with cross-functional teams.

Nice to Have
Experience building data infrastructure for machine learning workloads.
Experience defining SLIs/SLOs for data pipelines.
Knowledge of data governance, lineage, and compliance practices.
Experience with capacity planning and infrastructure cost optimization.
Experience improving or modernizing existing data platforms.

What You'll Get
Fully remote position with flexible working hours.
High ownership and direct impact on architecture and product direction.
Work on systems operating at significant scale.
Fast-paced startup environment with experienced leadership.
Competitive compensation based on experience and skill set.