Big Data Consultant / Engineer

Candidate Description

With over eight years immersed in data-engineering and analytics, this professional excels at architecting and optimising large-scale platforms across consulting, retail, transportation, and manufacturing sectors. Their expertise spans cloud ecosystems such as Azure and AWS, advanced tooling like Databricks and Apache Spark, and modern practices in generative AI, ML Ops, and cost-efficient lakehouse design. Adept communication and stakeholder-management skills underpin consistent delivery of high-value, data-driven outcomes.

Demonstrated technical acumen includes building resilient streaming pipelines with Kafka, crafting Azure Data Factory workflows, integrating Elasticsearch search experiences, and designing near-real-time CDC solutions. Key achievements encompass delivering a 90 % SLA for sub-300 ms search responses at a Major Retailer, implementing a green-field data platform that halved a Transportation Company's customer-facing latency, and leading ML initiatives that converted prototypes into enterprise engagements at a Technology Provider. Hands-on proficiency covers Python, Scala, SQL, Docker, TensorFlow, MLFlow, and robust data-governance frameworks.

Beyond deep technical capacity, they have repeatedly led and mentored small agile teams, harmonising cross-functional collaboration to meet demanding timelines and budgets. Their adaptable approach embraces emerging technologies generative AI, intelligent search, IoT telemetry and aligns them with strategic business goals. Whether driving cloud-migration roadmaps or fine-tuning mission-critical pipelines, this individual delivers scalable, future-proof solutions that empower organisations to unlock actionable insights and sustainable value.