We are currently partnering with one of our valued clients, a technology-driven organization, to find a skilled Data Engineer who will play a key role in building and optimizing scalable data systems that support operational and analytical workflows. This is a contract-based position with a fully remote working arrangement.
The Data Engineer will be responsible for designing data models, developing robust pipelines, and managing end-to-end data infrastructure, from ingestion and staging to serving layers. This role requires a strong technical foundation, hands-on database expertise, and the ability to ensure performance, reliability, and data quality across systems.
Responsibilities:
- Design conceptual, logical, and physical data models for operational and analytics use cases.
- Define schemas for both OLTP and OLAP workloads.
- Implement schema standards, including naming conventions, constraints, and referential integrity.
- Optimize database performance through indexing, partitioning, query tuning, and materialized views.
- Build and maintain scalable ETL/ELT pipelines for structured and unstructured data.
- Develop batch and near-real-time ingestion workflows.
- Ensure pipelines are fault-tolerant, observable, and production-ready.
- Implement data validation and quality checks.
- Maintain clear data lineage and structured logging/metrics.
- Support compliance, auditability, and resilience practices (backup, replication, failover).
- Collaborate cross-functionally with engineering, DevOps, security, and product teams.
Requirements:
- Minimum 5 years experience in data engineering or backend data systems with ownership of production pipelines.
- Bachelor's Degree in Computer Science, IT, Data Engineering, Software Engineering, or related field.
- Strong proficiency in SQL and hands-on experience with PostgreSQL (schema design & performance tuning).
- Proven expertise in data modeling for transactional and reporting systems.
- Proficiency in Python (or similar) for pipeline development and automation.
- Experience with object storage systems (e.g., S3-compatible).
- Solid understanding of partitioning, indexing, and materialized views.
- Experience with monitoring, logging, and reliability practices in production environments.
- Familiarity with search technologies (e.g., OpenSearch or Elasticsearch).
- Exposure to AI/ML data workflows.
- Experience working in secure or regulated environments.
