Technical Lead

Ness Digital Engineering

About The Position

We are looking for an inspiring and forward-thinking Business Analyst to craft, evolve, and champion our enterprise data platform. You will play a pivotal role in empowering smarter decisions, accelerating innovation, and enabling AI-driven opportunities across the organisation. In this high-impact role, you will set the vision and lead the delivery of a modern, scalable, and trusted data architecture that not only meets today’s business needs but positions us for tomorrow’s breakthroughs. Your expertise will help teams unlock the full value of data — turning it into a competitive advantage.

Requirements

Proven experience in data analysis.
Proven experience in financial industry.
Expertise in cloud-native data platforms (e.g., Snowflake, Databricks, BigQuery, Amazon Redshift).
Advanced data modeling skills (conceptual, logical, physical) across relational, NoSQL, and event-driven systems.
Hands-on proficiency with ETL/ELT tools (e.g., dbt, Fivetran, Matillion) and streaming technologies (e.g., Kafka, Kinesis, Pulsar).
Strong knowledge of data governance platforms (e.g., Collibra, Alation, Informatica) and industry best practices.
Understanding of AI/ML data lifecycle management and operationalisation.
Exceptional communication skills with the ability to inspire, influence, and align diverse stakeholders.

Responsibilities

Shape and deliver an enterprise-wide data architecture strategy that fuels growth and innovation.
Define reference architectures, canonical data models, and integration patterns to create a consistent, reliable, and agile data foundation.
Curate and integrate cutting-edge modern data stack technologies to speed delivery and maximise value.
Design, deliver, and optimise data pipelines, APIs, and real-time streaming frameworks that power business-critical insights.
Embed data quality, lineage, and metadata management into every solution for trusted and transparent data.
Prepare and enrich enterprise data to unlock the potential of AI, ML, and predictive analytics.
Lead the rollout of data governance, compliance, and privacy frameworks that inspire confidence and meet global standards.
Partner with security and compliance teams to build safe, accessible, and well-managed data environments that enable innovation.
Act as a strategic advisor to executives, connecting technical architecture with measurable business outcomes.
Work hand-in-hand with cross-functional teams to embed data-driven thinking into every decision.
Mentor colleagues, champion best practices, and foster an inclusive, high-energy culture of data excellence.