Templeton & Partners - Innovative & Inclusive Hiring Solutions
Data Architect
London
Posted about 15 hours ago
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As a Data Tech Lead
As a Data Tech Lead, you will provide end-to-end leadership across architecture, engineering, governance, and capability development.
You will:
- Deliver sustainable and innovative solutions to unlock value from data.
- Lead the architecture, design, and implementation of on-premises/cloud-based application development and data solutions.
- Engage cross-functional teams to support project stakeholders in delivering data scope and operational excellence.
- Drive governance, metadata management, data modelling, cost optimization, high-volume performance tuning, and agility in delivery.
- Engage effectively with senior leadership, resolve conflicts proactively, and represent the data organization with confidence and clarity.
Key Responsibilities
Leadership & Strategy
- Drive the architecture, design, and delivery of data ecosystems for futuristic data platforms.
- Define data product roadmaps and drive the development of data solutions using approved tech stack and related technologies.
- Align data engineering initiatives with long-term business and technology strategies.
- Provide technical leadership to ensure adherence to best practices, standards, and quality expectations.
Technical Oversight
- Lead data modelling and architecture using tools such as SAP PowerDesigner and WizDesign.
- Develop and optimize intelligent, AI-augmented data pipelines across ADF, ADLS, Databricks, DLT, and Structured Streaming to enable high-performance data delivery.
- OLTP schema design, normalization, indexing strategy, performance tuning for transactional systems.
- Transaction management, concurrency, deadlocks.
- PostgreSQL, MySQL, SQL Server expertise (depending on company's standards).
- Optimize Databricks workloads with a strong focus on performance and cost efficiency.
- Implement robust security, governance, lineage, and metadata controls using Unity Catalog.
- Troubleshoot pipeline issues, ensure high data quality, and enforce SLA compliance.
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Governance & Quality Assurance
- Establish data governance frameworks covering security, privacy, quality, and lifecycle management.
- Monitor pipeline performance and lead root cause analysis for data and process issues.
- Drive CI/CD and touchless change management frameworks to enable seamless deployments.
Stakeholder Management
- Collaborate closely with PMs, BAs, Data Scientists, Architects, and business stakeholders.
- Translate complex technical concepts into business terms for executive audiences.
- Resolve conflicts and ensure alignment across strategic priorities.
- Stakeholder management & executive communication.
Required Skills & Experience
- 12–17 years of experience in data engineering, data architecture, or analytics platforms.
Deep expertise in:
- Azure Data Engineering (ADF, ADLS, Databricks, DLT), AZURE Function, SQL, REST/FAST API, LogicApps.
- Databricks Delta Live Tables & Structured Streaming.
- Unity Catalog governance and lineage.
- Strong hands-on skills in SQL, Python, Spark/Scala.
- Strong experience in data modeling, data architecture, and metadata management.
- CI/CD for application delivery (Azure DevOps/GitHub Actions).
- Containerization (Docker), Kubernetes basics.
- API gateway, reverse proxies, load balancing.
- Solution Data Architecture, Data Modeling tools like SAP PowerDesigner, BiZ Design.
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AI & Future-Ready Skills
- Working knowledge of AI/ML, GenAI, Agentic AI, and applying AI for data engineering automation.
- Ability to envision and build future-ready, scalable data ecosystems.
Soft Skills / Leadership Competencies
- Proven ability to lead mid-sized to large technical teams.
- Strong decision-making capabilities backed by data.
- Exceptional communication and executive presentation skills.
- Conflict management and stakeholder alignment experience.
- High accountability, ownership, and ability to drive independent outcomes.
- Adaptability and continuous learning mindset.
Nice to Have
- Experience with Kafka, Hadoop, Spark Streaming.
- Experience with workflow tools like Airflow, Azkaban, Luigi.
- Knowledge of PowerBI/QlikSense visualizations.
- Certifications in Azure Data Engineer, Databricks, AI/ML, or Data Science.
- Experience with GitHub/Azure DevOps, CI/CD, Agile/Kanban methodologies.
- Understanding of Freight Domain like Voyage Management, Chartering, Freight Pricing, Demurrage, Laytime, Port calls, Vessel scheduling.
- Integration with RightAngle, Endur, Veson IMOS, or internal Company,'s Freight systems.
- Knowledge of T&S business processes.
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Jessica, London
Skills
Data Engineering
Data Architecture
Azure Data Engineering
SQL
Python
Spark
Data Modeling
Metadata Management
CI/CD
Containerization
API Gateway
Data Governance
Performance Tuning
AI/ML
Databricks
PostgreSQL
Location