Build and scale the data backbone for HR, payroll, finance, and insurance products. Design data models across warehouses and data lakes, develop and optimize batch and real-time ETL/ELT pipelines, improve data quality and governance, tune SQL queries, address data integration gaps, and collaborate with engineering, BI, analytics, and business stakeholders.
This is a remote position.
Organization: Confidential client in HR industry; subject to client confidentiality requirements
Location: Remote - open to candidates in Egypt, Jordan, Lebanon, Palestine, or Oman
Role Type: Full-time | Consultant-contractor | Fixed term (12-18 months)
Reports to: To be confirmed
The opportunity
Our client is looking for a Middle+ Data Engineer to build and scale the data backbone behind their HR, Payroll, Finance, and Insurance products. In this role, you will design data models, build and optimize ETL/ELT pipelines, and strengthen data quality and governance, collaborate with engineering and BI stakeholders, and help deliver unified, trustworthy data across the platform.
About the organization
Our client is a UAE-based HRTech scale-up transforming workplace operations across HR, Payroll, Finance, and Insurance in the MENA region. It helps employers and employees manage the full workplace lifecycle through a unified platform. The data team is currently focused on maturing the organization's data warehouse, governance, and reporting infrastructure to support the company's continued growth.
What you will do
- Own the design and maintenance of scalable data models (3NF, Dimensional, Data Vault) across the data warehouse and data lakes.
- Build, optimize, and monitor batch and real-time ETL/ELT pipelines and automation workflows to standards of reliability and performance.
- Partner with BI and analytics stakeholders to tune complex SQL queries and enable fast, reliable reporting.
- Use data governance, lineage, and Master Data Management (Customer 360) practices to improve data quality and integrity.
- Identify and address gaps in data integration across external and internal sources.
- Communicate progress, priorities, and trade-offs clearly to engineering and business stakeholders.
What you bring
- Demonstrated ability to design and optimize complex data models and pipelines, shown through 3-4 years of professional Data Engineering experience.
- Experience with cloud Data Warehouses (BigQuery or Snowflake) and the AWS ecosystem, or a closely related equivalent.
- Strong written and verbal communication in English (B1+).
- The ability to work independently and collaboratively across distributed, cross-functional teams.
- Strong proficiency in SQL (complex query optimization) and Python.
Helpful, but not essential
- Exposure to HRTech, fintech, or insurance domains.
- Experience in startup or scale-up environments.
- Familiarity with BI and data visualization tools such as Looker or Superset.
How the engagement works
Contracting party: You will contract directly with Apricot, which will manage contracting, invoicing/payroll, payments, and administrative support. Day to day, you will work with the client's data and engineering teams and report to the Data/Engineering Lead.
For this consultant/contractor engagement, your work will be based on the agreed scope and deliverables. You are expected to provide your own laptop and basic equipment, maintain reliable connectivity and a secure working environment, and follow required security controls, including two-factor authentication.
Any client-provided specialized equipment, leave, stipend, wellbeing benefit, or other support will be stated separately as an approved exception.
Planned check-ins are at month 1 and month 3 to see how the engagement is working and help address issues.
About Apricot
Apricot is a nonprofit sourcing firm connecting displaced and underserved professionals from Palestine and the wider MENA region with global employment opportunities. We combine a clear social-impact mission with fast, high-quality recruitment delivery for international clients.
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design and operate scalable batch and streaming data platforms supporting machine learning and generative AI. Build pipelines for structured, unstructured, OCR, document, and image data; develop RAG, semantic search, and LLM-powered solutions; and establish data quality, observability, governance, orchestration, and deployment practices. Partner with stakeholders, lead platform scalability and cost optimization, mentor engineers, and translate ambiguous needs into production-ready technical roadmaps while securely handling sensitive data.
Top Skills:
AirflowAmazon KinesisSparkAWSAzureAzure Event HubsChart.JsDatabricksDeequDelta LakeDockerGithub ActionsGCPGreat ExpectationsJavaKafkaKubernetesLlmsMlopsPlotlyPysparkPythonRagScalaSeabornSnowflakeSQLTerraform
Artificial Intelligence • Information Technology • Professional Services • Software • Analytics • Generative AI • Big Data Analytics
Configure and maintain Adobe Experience Platform and Real-Time CDP data pipelines, XDM schemas, datasets, identity resolution, Profile enablement, segmentation readiness, and destination activation. Validate data quality, troubleshoot ingestion and identity issues, manage sandboxes, and implement privacy, consent, governance, and access controls. Partner with architects, data engineers, consultants, analysts, data scientists, and marketing teams to support reporting, personalization, and machine learning readiness.
Top Skills:
Adobe AnalyticsAdobe Experience PlatformAdobe I/O RuntimeAdobe Journey OptimizerAdobe Real-Time CdpAdobe Source ConnectorsAdobe TargetAPIsAWSAzureBatch IngestionBigQueryCcpaData PrepEltETLGCPGdprJavaScriptPythonQuery ServiceRedshiftSalesforce CdpSegmentSnowflakeSQLStreaming IngestionWeb SdkXdm
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Lead cloud data modernization by designing and implementing Azure/Snowflake/Databricks data platforms, building scalable ETL/ELT pipelines, ensuring data quality, security and governance, implementing CI/CD, mentoring engineers, and supporting healthcare data solutions and compliance.
Top Skills:
AirflowAzureAzure Data Factory (Adf)Azure Data Lake Storage Gen2 (Adls Gen2)Change Data Capture (Cdc)CptDatabricksDatabricks GenieEtl/EltFacetsFhirGitGithub ActionsGithub CopilotHcpcsHl7Icd-10LlmsLoincPrompt EngineeringPysparkPythonRag PipelinesSnowflakeSnowflake CortexSparkSQL ServerSsisVector StoresVisioX12 Edi (837/835/834)
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories


