Senior Data Engineer AI Solutions

📋 Description

• • Lead the design, development, and scaling of enterprise-grade data pipelines that power AI-driven products for Fortune-500 clients across North America, EMEA, and APAC.
• • Architect cloud-native ETL/ELT workflows on Microsoft Azure (Data Factory, Synapse, Databricks, Purview) that ingest and transform multi-terabyte data sets from ERP, CRM, IoT, and social sources with sub-second latency SLAs.
• • Own the end-to-end data lifecycle—from raw ingestion through curated gold-zone datasets—ensuring data quality, lineage, and governance are embedded via automated testing, CI/CD, and policy-as-code.
• • Partner with data scientists and AI researchers to productionize machine-learning models (PyTorch, TensorFlow, Azure ML) by building feature stores, real-time scoring APIs, and MLOps pipelines that reduce model-deployment time from weeks to hours.
• • Drive the adoption of modern data mesh principles, enabling domain-oriented ownership and self-serve analytics while maintaining centralized security and compliance controls (GDPR, HIPAA, SOC 2).
• • Mentor a distributed team of 4–6 data engineers through code reviews, pair programming, and technical guilds, fostering a culture of experimentation, blameless post-mortems, and continuous learning.
• • Collaborate with product managers and client stakeholders to translate complex business requirements into technical epics, accurate estimates, and iterative delivery plans aligned to OKRs and quarterly roadmaps.
• • Optimize cloud spend and performance by implementing auto-scaling, incremental load strategies, and cost-aware query patterns, achieving 25–40 % savings on data-platform budgets.
• • Champion data observability by integrating logging, metrics, and alerting (Azure Monitor, Data Dog, Prometheus) that proactively surface anomalies and reduce mean-time-to-recovery (MTTR) to under 15 minutes.
• • Contribute to Quisitive’s IP portfolio by authoring reusable accelerators, open-source contributions, and thought-leadership blogs that showcase best practices in AI-ready data engineering.
• • Present technical deep-dives and success stories at Microsoft Ignite, Data & AI Summit, and internal Quisitive Tech Talks, elevating both your personal brand and the company’s market presence.
• • Influence strategic technology decisions by evaluating emerging Azure services (Fabric, Copilot Studio, Real-Time Intelligence) and creating proof-of-concepts that guide multimillion-dollar investment roadmaps.