Senior 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 platform.
• Define data product roadmaps and drive development of data solution 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 Shell 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.

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.

4. 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

Technical Expertise

• 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

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 Shell Freight systems
• Knowledge of T&S business processes