Job Summary We are seeking an experienced Data Engineering Architect / Lead Data Engineer to design, build, and optimize scalable data platforms and pipelines. The ideal candidate will have extensive experience in ETL/ELT development, cloud-based data engineering, real-time and batch data processing, and modern data warehouse architectures. This role requires strong expertise in designing end-to-end data solutions that are scalable, secure, and aligned with enterprise standards.
Required Skills & Qualifications
- Advanced expertise in designing and developing ETL/ELT pipelines
- Strong experience with batch data processing and near real-time/streaming data pipelines
- Hands-on experience working with structured and semi-structured data
- Strong knowledge of: Incremental data loading Change Data Capture (CDC) Pipeline orchestration and dependency management
- Strong programming skills in Python (preferred), Scala, or Java
- Experience optimizing large-scale data processing workloads for performance and cost
- Solid understanding of data modeling concepts: Star Schema Snowflake Schema Normalized and denormalized data models
- Hands-on experience with at least one major cloud platform: Microsoft Azure Amazon Web Services (AWS) Google Cloud Platform (Google Cloud Platform)
- Strong experience with modern data warehouses such as: Snowflake Azure Synapse Google BigQuery Amazon Redshift
Key Responsibilities
- Data Architecture & Solution Design Design end-to-end data engineering architectures for enterprise-scale solutions
- Develop scalable architectures for: Data Lakes and Lakehouse platforms Enterprise Data Warehouses Streaming and real-time data processing systems
- Ensure solutions align with enterprise architecture, security, governance, and compliance standards
- Review and approve technical designs and implementation strategies
- Data Pipeline Development & Management Lead the design and development of scalable ETL/ELT pipelines
- Build and manage data ingestion pipelines for both batch and real-time data
- Process structured and semi-structured data efficiently
- Optimize data pipelines for performance, reliability, scalability, and cost
- Manage schema evolution, metadata, and pipeline dependencies
- Data Quality, Reliability & Operations Establish and enforce data quality standards and validation frameworks
- Implement monitoring, alerting, logging, and observability for data pipelines
- Perform root cause analysis and resolve data-related production issues
- Drive operational excellence by improving system stability and reliability
- DevOps / DataOps Build and maintain CI/CD pipelines for data engineering workloads
- Automate testing, deployment, and rollback processes
- Improve platform reliability and deployment efficiency through automation and DevOps best practices
Preferred Qualifications Experience with modern DataOps and CI/CD practices. Knowledge of data governance, security, and compliance frameworks. Experience designing enterprise-scale cloud-native data platforms. Strong analytical, troubleshooting, and communication skills.
For applications and inquiries, contact:[email protected]
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
