Job description

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.
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.