Data Engineer
ITGOALS New Cairo City, Cairo, Egypt · $12K–$24K/yr
Software Development · 51-200 employees
About the role
Design, build, and maintain reliable data pipelines and ETL/ELT processes to support analytics, AI, and operational reporting. Collaborate with cross-functional teams to ensure data quality, lineage, and accessibility within a regulated financial-services environment.
What they look for
Requirements
Requires 5+ years of experience in data engineering with strong proficiency in SQL and Python. Candidates should have practical experience with relational databases, data modeling, and data governance in enterprise environments.
Full description
## About ITGOALS ITGoals is an Egypt-based enterprise software and technology delivery company with 17+ years of enterprise delivery experience. We provide dedicated engineering teams, ERP and SAP services, product engineering, software development, and outsourcing / nearshore delivery for organizations across the GCC, Europe, the United States, and the wider region. Our financial-services work includes secure platforms and technology delivery supporting banking, payments, digital channels, integration, data, and financial operations.
## Job Title Data Engineer
## Location Cairo, Egypt (hybrid/work-from-office supported; international collaboration as needed)
## Years of Experience 5+ years in data engineering or related roles
## Job Description As a Data Engineer at ITGoals, you will design, build, and maintain reliable data pipelines and data assets that enable analytics, operational reporting, AI use cases, and data-driven decision making within an enterprise financial-services environment. You will collaborate with analysts, AI developers, application teams, and governance teams to ensure data quality, lineage, and accessibility across regulated environments.
## Key Responsibilities * Design, build, test, and maintain batch and near-real-time data pipelines for ingestion, transformation, enrichment, and delivery of trusted data. * Develop ETL / ELT processes that move data reliably between source systems, data platforms, analytical stores, and consuming applications. * Write efficient SQL and Python code for data transformation, validation, automation, reconciliation, and operational support. * Create reusable data models and datasets that are understandable, documented, and suitable for reporting, analytics, and AI workloads. * Implement data-quality controls covering completeness, validity, consistency, duplication, reconciliation, and exception handling. * Work with structured and semi-structured data from enterprise applications, APIs, files, databases, and integration platforms. * Support lineage, metadata, documentation, access-control, and governance requirements appropriate for regulated data environments. * Optimize pipeline performance, scheduling, reliability, and resource usage while maintaining clear monitoring and alerting. * Collaborate with analysts, AI developers, application teams, architects, security, and infrastructure teams to deliver end-to-end data solutions. * Participate in CI/CD, code review, testing, environment promotion, and production-support processes for data workloads. * Troubleshoot failed jobs, data inconsistencies, performance bottlenecks, and upstream / downstream dependency issues.
## Required Experience * Hands-on experience engineering data pipelines and transforming data in enterprise or production environments. * Strong practical experience with SQL and at least one general-purpose data engineering language, preferably Python. * Experience working with relational databases, data warehouses / lakehouse concepts, and scheduled data-processing workloads. * Understanding of data quality, reconciliation, governance, and operational support.
## Required Skills * Advanced SQL * Python for data engineering * ETL / ELT concepts and pipeline design * Relational data modelling * Data quality and reconciliation * APIs / files / database ingestion patterns * Git and collaborative development practices * Monitoring, troubleshooting, and production support * Documentation and data-governance awareness
## Banking / Fintech & Nice to Have * Banking, fintech, payments, risk, finance, customer analytics, or other regulated financial-services data experience is a strong advantage. * Experience with cloud data platforms, Spark, Kafka, Airflow, dbt, or comparable technologies. * Data warehouse, lakehouse, or data-lake implementation experience. * Experience preparing data for machine-learning or AI workloads. * Understanding of personally identifiable information, access controls, data retention, and audit requirements.
## What Success Looks Like * Treats data reliability and traceability as engineering requirements, not afterthoughts. * Can explain where data came from, how it changed, and how quality is validated. * Builds pipelines that are maintainable, observable, and supportable by a wider team.
## ITGOALS Offers * Enterprise-scale assignments where engineering quality, security, resilience, and delivery discipline matter. * Structured ITGoals recruitment, onboarding, delivery governance, and clear professional ownership throughout the engagement. * Collaboration with experienced engineers, architects, QA professionals, delivery leaders, and business stakeholders. * Exposure to complex digital-transformation environments and the opportunity to deepen banking, fintech, payments, and regulated-enterprise experience. * Opportunities to contribute to long-term enterprise delivery programs based on performance, business demand, and role fit.
## Application Instructions Share an updated CV with the ITGoals recruitment team, highlighting the experience most relevant to this role, particularly enterprise delivery, banking / fintech exposure where applicable, and the technologies listed above. Shortlisted candidates will be contacted for the next stage of the recruitment process.
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