Head of Data Engineering

The Head of Data Engineering is responsible for leading the design, build, and operation of scalable, secure, and high-performing data platforms and data pipelines across ZainTECH and its customers. This role will own the data engineering strategy, standards, and execution across on-premises, private cloud, and public cloud environments, ensuring that data is reliable, timely, and ready for analytics, AI, and business consumption.

The ideal candidate will have a strong background in modern data platforms, big data, cloud data services, and software engineering practices, with a proven track record of delivering complex data solutions that meet business, security, and regulatory requirements.

Responsibilities:

Platform & Architecture (On Prem, Cloud, Hybrid)

• Own the end-to-end architecture and evolution of data platforms, including on prem (e.g., Cloudera / Hadoop), private cloud, and public cloud (e.g., Azure, AWS, GCP).
• Define and champion reference architectures for: o Data lakes, data warehouses, and lake houses. o Real-time and batch data integration. o Metadata, lineage, and observability.
• Collaborate with Enterprise / Solution Architects to: o Evaluate and select technologies, tools, and services. o Ensure scalability, performance, reliability, and cost-efficiency.
• Design hybrid data patterns (e.g., PII kept on-prem, analytics/AI in cloud, edge to-cloud integration) to meet local regulatory and data residency requirements.
  
  

Leadership & Collaboration

• Build, lead, and mentor a high-performing data engineering team, including hiring, performance management, career development, and succession planning.
• Foster a culture of engineering excellence, continuous learning, and innovation within the team.
• Collaborate closely with: o Cloud, Cybersecurity, and Infrastructure teams (environment, access, security). o Digital Solutions and Application teams (APIs, integration with apps and services). o Sales and Presales (feasibility checks, solution design, effort estimation for RFPs).
• Promote strong collaboration with client and partner teams, ensuring clear communication of technical decisions, risks, and trade-offs.
  
  

Delivery, Operations & Reliability

• Lead the end-to-end delivery of data engineering projects and workstreams, from design and build through testing, deployment, and transition to operations.
• Oversee the implementation of CI/CD and automation for data pipelines, including testing, deployment, and monitoring.
• Ensure data platforms and pipelines meet defined SLAs, SLOs, and non functional requirements (performance, availability, security, resilience).
• Implement and monitor data observability and quality controls (e.g., data validation, anomaly detection, lineage tracking).
• Work with Operations teams to establish runbooks, incident management, and continuous improvement of platform reliability
  
  

Technology & Innovation

• Stay up-to-date with industry trends and emerging technologies in big data, cloud data services, real-time analytics, and MLOps.
• Evaluate and recommend new tools, platforms, and approaches that improve speed, quality, and cost of data delivery.
• Drive innovation initiatives, PoCs, and accelerators (e.g., new ingestion patterns, real-time data mesh, metadata-driven pipelines).
• Provide input into productization and packaging of ZainTECH data offerings (e.g., reusable blueprints, managed data platform services).
  
  

Opportunity & Solution Shaping

• Work closely with Sales and Account Managers to qualify opportunities and identify client challenges across data platforms, data governance, analytics, and AI.
• Lead solution discovery workshops with customers to understand business objectives, current architecture, constraints (e.g., data residency, security, PII on-prem), and success criteria.
• Translate business requirements into high-level and detailed solution designs, covering:
• Data ingestion and integration (batch, real-time/streaming). o Data lake / data warehouse / lakehouse architectures
• BI & self-service analytics.
• AI/ML workloads and MLOps.
• Data governance, catalog, and quality
  

RFP / RFI / Proposal Leadership

• Own the technical sections of RFP/RFI responses for data and AI solutions across multiple technologies (on-prem and cloud).
• Analyze RFP requirements, scope, and scoring criteria; design winning strategies and answer templates for technical, functional, and non-functional requirements.
• Coordinate with internal teams (Data Engineering, Architecture, Delivery, Finance) to: o Estimate efforts and timelines.
• Define implementation phases and milestones.
• Prepare BoQ/BOM, licensing estimates, and cost assumptions.
• Prepare clear, structured proposal content including solution overviews, architectures, implementation plans, assumptions, risks, and value propositions.
• Ensure proposals are aligned with ZainTECH standards, reusable accelerators, and partner best practices
  

Architecture & Technology (On Prem and Cloud)

• Design hybrid architectures leveraging both on-premise platforms (e.g., Cloudera, Hadoop ecosystem) and cloud (Azure, AWS, GCP), depending on client constraints and preferences.
• Define reference architectures for:
• On-prem data platforms (e.g., Cloudera CDP, Hadoop/Spark, on-prem object storage).
• Cloud-native data platforms (e.g., Azure Synapse/Fabric, AWS Redshift/EMR, GCP BigQuery/Dataproc).
• Hybrid scenarios (data gravity on-prem, analytics or AI in cloud, PII data residency, etc.).
• Collaborate with Delivery and Architecture teams to validate feasibility, performance, and scalability of proposed solutions.
  
  

Demonstrations, PoCs, and Client Engagement

• Prepare and deliver technical presentations, live demos, and tailored PoCs for data platforms, governance, analytics, and AI use cases.
• Build or supervise PoC architectures and quick prototypes showcasing:
• Ingestion from key source systems (ERP, CRM, billing, sensors, logs, etc.).
• Data models and curated layers.
• Analytics dashboards and AI/ML use cases (e.g., churn, recommendation, anomaly detection).
• Collect client feedback and incorporate into solution refinement and product/offer roadmap
  
  

Collaboration with Vendors and Partners

• Work closely with strategic partners (e.g., Microsoft, Cloudera, Informatica, Databricks, etc.) to:
• Align on recommended architectures and best practices.
• Validate sizing, licensing, and deployment patterns (on-prem, IaaS, PaaS, SaaS).
• Prepare joint presentations, PoCs, and reference architectures.
• Ensure ZainTECH's proposals leverage partner programs, incentives, and co selling frameworks where applicable.
  
  

Internal Enablement and Knowledge Sharing

• Document reusable solution templates, RFP answer libraries, architecture blueprints, and effort-estimation models for future opportunities.
• Provide training and knowledge-sharing sessions to:
• Sales and presales teams (value messaging, positioning, competition).
• Delivery teams (solution rationale, assumptions, architecture decisions).
• Stay current on industry trends, data & AI reference architectures, and competitors, and feed market insights into ZainTECH offerings and go-to-market strategy.
  
  

Requirements

• 15+ years of experience in data engineering, data platforms, or related fields, with at least 5 years in a leadership role managing engineering teams.
• Proven experience designing, building, and operating large-scale data platforms and pipelines in on-prem and cloud environments.
• Strong hands-on background in on-prem big data platforms such as Cloudera CDP, Hadoop, Spark, Kafka, Hive, HBase, and NiFi
• Experience with cloud data services including Azure Synapse, Fabric, Azure Data Lake, Databricks, AWS S3, Redshift, Glue, EMR, and GCP BigQuery and Dataproc
• Proficiency in containerization and orchestration tools like Docker and Kubernetes
• Deep understanding of data modeling and data architecture patterns (relational, dimensional, lakehouse, streaming)
• Solid knowledge of data integration patterns (batch, streaming, CDC, event-driven)
• Strong grasp of data quality, observability, security, and access control principles
• Proven ability to lead cross-functional engineering initiatives end-to-end
• Experience in defining and enforcing standards, frameworks, and engineering best practices
• Ability to collaborate with senior stakeholders to translate business needs into technical solutions
• Excellent presentation, communication, and storytelling skills, with the ability to explain complex architectures in simple business language
• Experience creating architecture diagrams and solution design documents
• Experience developing high-level implementation plans, including assumptions and risk registers
• Experience preparing rough order of magnitude (ROM) and effort estimations
• Experience working with regulated industries such as telecom, financial services, and government is an advantage
• Familiarity with data residency and compliance requirements is an advantage
• Arabic speaking is preferred
• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field; Master's degree preferred
• Professional certifications in cloud and data technologies (e.g., Azure Data Engineer / Architect, AWS Data Analytics, GCP Data Engineer, Cloudera, Databricks, Snowflake).
• Certifications or formal training in Agile, DevOps, or SAFe are a plus