Senior Data Engineer

About Us
True Path Leads is a fast-growing performance marketing company building high-load infrastructure for lead generation at scale. We process millions of events daily across complex integrations with external partners. Quality is critical — and we're looking for a Senior Manual QA Engineer who can own it.

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.
Languages: English B2, Russian or Ukrainian — native.
Located in a European time zone.

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 within a European timezone.
Work on high-load, real-world systems with complex data flows.
Direct collaboration with engineering and product teams.
Fast-paced startup environment with experienced leadership.
Competitive compensation based on experience and skill set.
Clear growth path in a scaling product company.