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Senior Data Engineer

1 month ago
Egypt
Full-time
Senior
Data Engineer
Software Development
Apache Airflow Apache Spark AWS Azure CI/CD Dagster Databricks dbt Docker Encryption Feature Engineering GCP Git Java Kafka Kubernetes Looker Metabase MLOps Power BI Prefect Python Scala Secrets Management Snowflake SQL Superset Tableau Terraform
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PetroApp

PetroApp

PetroApp is a smart NFC-based system for efficient vehicle expense management and fuel monitoring, integrating gas stations and service centers for precise budget control and waste reduction.

Gas Utilities
51-250
Founded 2018
View All Jobs 2

Description

  • Design and maintain scalable batch and near-real-time data pipelines across mobile apps, transactions, station integrations, ERP systems, payments, support systems, and operational databases.
  • Create clean, reusable data models for core business entities and analytics use cases.
  • Implement data validation, lineage, observability, alerting, reconciliation, and automated quality checks to ensure accurate and timely reporting.
  • Partner with analytics, product, finance, operations, and customer success teams to deliver self-service datasets, metrics layers, and documented data marts.
  • Tune queries, storage layouts, orchestration schedules, and cloud resources to improve performance and reduce infrastructure cost.
  • Apply data access controls, PII handling, retention practices, auditability, and compliance-aware engineering patterns across the data lifecycle.
  • Build robust ingestion patterns for APIs, webhooks, CDC, files, event streams, third-party integrations, and partner data feeds.
  • Use CI/CD, version control, automated testing, infrastructure-as-code, and deployment standards for data pipelines and transformations.
  • Troubleshoot data incidents, perform root-cause analysis, reduce recurring failures, and communicate impact to stakeholders.
  • Review designs and code, establish engineering standards, mentor junior team members, and help raise the quality bar for the data organization.

Requirements

  • 5+ years of professional experience in data engineering, analytics engineering, platform engineering, or backend engineering with strong data ownership.
  • Advanced SQL skills, including query optimization, data modeling, window functions, incremental transformations, and large-table performance tuning.
  • Strong Python programming experience for data pipelines, automation, testing, and production-grade data workflows.
  • Hands-on experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or similar.
  • Experience with modern data warehouses or lakehouse platforms such as BigQuery, Snowflake, Redshift, Databricks, Delta Lake, Iceberg, or equivalent.
  • Experience building reliable ELT/ETL pipelines using dbt, Spark, Kafka, Flink, Fivetran, Stitch, custom API ingestion, or CDC frameworks.
  • Practical understanding of data quality, schema evolution, monitoring, alerting, backfills, idempotency, and failure recovery.
  • Experience designing dimensional, wide-table, and event-based data models for BI, analytics, and operational reporting.
  • Comfort working with cloud platforms such as AWS, GCP, or Azure, plus Git-based engineering workflows.
  • Strong communication skills with the ability to translate business requirements into technical designs and delivery plans.
  • Experience in fintech, payments, fleet management, logistics, mobility, marketplace, fuel, or high-volume transaction platforms is preferred.
  • Knowledge of event-driven architectures, streaming data, CDC, API integrations, data contracts, and data mesh or domain-oriented data ownership is preferred.
  • Experience supporting BI tools such as Power BI, Looker, Tableau, Metabase, Superset, or similar platforms is preferred.
  • Familiarity with MLOps or feature engineering for fraud detection, anomaly detection, forecasting, customer segmentation, or optimization use cases is preferred.
  • Experience with data privacy, access control, encryption, secrets management, and compliance expectations in the Middle East or multi-country operations is preferred.
  • Comfort with SQL and Python, with optional Scala or Java for distributed processing.
  • Experience with dbt or equivalent transformation tools, dimensional modeling, and metrics layers.
  • Experience with Airflow, Dagster, Prefect, or similar orchestration tools.
  • Experience with cloud warehouses, data lakes/lakehouses, object storage, and distributed processing environments.
  • Experience with Kafka or equivalent streaming tools, CDC, APIs, webhooks, files, and partner data feeds.
  • Experience with Git, CI/CD, automated tests, Docker, Kubernetes or containerized deployment, and Terraform or other infrastructure-as-code tools.
  • Experience with data quality checks, lineage, pipeline monitoring, logs, alerts, runbooks, and service-level objectives for data products.

Benefits

  • Competitive salary and benefits package.
  • Opportunity to work on cutting-edge technology with a passionate team.
  • Career growth and development opportunities.
  • A collaborative and inclusive work environment.

Interested in this position?

Apply directly on the company website

Apply Now

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