Data Engineer

Soum

. Design, build, and maintain scalable and reliable data pipelines for analytics, ML models, and business reporting .

Posted 10/26/2026full-timeRemote • Nigeria, Egypt, UzbekistanJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines, with proficiency in Python and SQL for data engineering tasks. Strong understanding of ETL/ELT processes, data warehousing, and cloud platforms, ensuring data quality and governance.

Highest-signal resume keywords

Python ProficiencySQL ProficiencyETL/ELT ProcessesCloud Platforms (AWS, GCP, Azure)Data Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignData ModelingQuery OptimizationData Quality ChecksData Warehousing

Soft Skills

Cross-Functional CollaborationRequirements Elicitation

Tools & Technologies

AirflowAirbyteDockerKubernetesDataform

Industry Keywords

Data GovernanceReal-Time Data ProcessingData Storage SolutionsData LakesData Warehouses

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSAzureBigQueryCloudDockerETLGoogle Cloud PlatformKafkaKubernetesPythonSparkSQL

About the role

Key responsibilities & impact

Design, build, and maintain scalable and reliable data pipelines for analytics, ML models, and business reporting
Collaborate with data scientists and analysts to ensure data is available, clean, and optimized for downstream use
Implement data quality checks, monitoring, and validation processes
Design efficient ETL/ELT workflows and integrate databases, APIs, and third-party tools into centralized data lakes or warehouses
Support cloud-based infrastructure for data storage and retrieval
Monitor, troubleshoot, and optimize existing pipelines for large-scale, real-time data flows
Apply best practices for query optimization and cost-efficient storage
Partner with product, engineering, and business stakeholders to gather requirements
Document workflows, schemas, and processes while supporting reliability, governance, and security

Requirements

What you’ll need

Proficiency in Python and SQL for data engineering tasks
Strong understanding of ETL/ELT processes, data warehousing, and data modeling
Hands-on experience with cloud platforms (AWS, GCP, or Azure) and data storage solutions (BigQuery, Redshift, Snowflake, etc.)
Familiarity with data orchestration tools; Airflow and Airbyte are a must
Experience with containerization and deployment tools (Docker, Kubernetes) is a plus
Knowledge of data governance, security, and best practices for handling sensitive data
Familiarity with Git and GitHub
Dataform is a must
Strong skills in eliciting requirements from cross-functional stakeholders and translating them into actionable data engineering tasks
Preferably 4 years of total experience
2+ years in data engineering, building and maintaining data pipelines
2+ years of SQL and Python development in production environments
Experience in fast-growing startup environments is a plus
Exposure to real-time data processing frameworks (Kafka, Spark, Flink) is a plus

Benefits

Comp & perks

Full-time employment
Remote work arrangement
Work directly with senior Finance leadership
Broad exposure across accounting, audit, and financial operations
Culture valuing ownership, speed, and constant improvement