Senior Data Engineer

About the Role
We are seeking a highly skilled and hands-on Senior Data Engineer to lead the design, development, and optimization of scalable data pipelines. You will play a critical role in architecting and maintaining the data infrastructure that supports enterprise analytics, business intelligence, and operational systems.

This position requires deep technical expertise in data integration, strong data architecture capabilities, and the ability to thrive in high-volume, business-critical data environments where performance, reliability, and scalability are essential.

Key Responsibilities

1. Pipeline Development & Data Integration
   Design, develop, and maintain robust ETL/ELT pipelines using Qlik Talend to process large datasets from diverse source systems
   • Implement reusable, scalable integration patterns across structured and semi-structured data sources
   • Ensure pipeline reliability through monitoring, logging, and automated validation mechanisms
   • Manage end-to-end data lifecycle from ingestion through transformation and delivery
2. Data Replication & Real-Time Processing
   Implement and manage log-based Change Data Capture (CDC) and near-real-time ingestion using Qlik Replicate
   • Support low-latency data availability for analytics and operational reporting
   • Oversee database replication strategies across heterogeneous systems
   • Ensure data consistency, reconciliation, and minimal downtime during migrations or platform upgrades
3. Data Architecture & Modeling
   Design and optimize scalable data models including Star Schema, Snowflake Schema, and Data Vault
   • Apply dimensional modeling principles and Kimball methodologies for analytics-ready data structures
   • Balance performance, storage efficiency, and maintainability in enterprise data warehouse environments
   • Contribute to architectural decisions regarding data platform evolution
4. Cloud & On-Premise Data Solutions
   Architect and manage hybrid data solutions across cloud platforms (AWS, Azure, GCP) and enterprise on-premise systems
   • Implement integrations with cloud data warehouses such as Snowflake, Redshift, BigQuery, or Synapse
   • Manage cloud storage solutions (S3, ADLS, GCS) for scalable data ingestion and processing
5. Performance Optimization & Governance
   Optimize complex SQL queries, transformations, and pipeline configurations for maximum efficiency
   • Conduct performance tuning across databases including PostgreSQL, SQL Server, and Oracle
   • Implement best practices for data quality, validation, and governance
   • Maintain documentation for pipelines, data models, and engineering standards
6. Collaboration & Mentorship
   Collaborate closely with Data Analysts, BI Developers, Data Scientists, and business stakeholders to translate requirements into scalable data solutions
   • Mentor junior data enginee
   
   https://www.executiveplacements.com/Jobs/S/Senior-Data-Engineer-1263100-Job-Search-02-17-2026-03-00-17-AM.asp?sid=gumtree