As an Architect – Data & AI at NCINGA, you will design and own enterprise-grade data and AI solution architectures spanning data engineering, machine learning, and intelligent automation. You will define end-to-end platform architectures covering ingestion, transformation, storage, orchestration, and AI/ML model deployment across cloud and hybrid environments. Working across pre-sales and delivery, you will translate complex client requirements into scalable, governed technical blueprints and guide engineering teams through implementation.
Key Responsibilities:
Design end-to-end data platform architectures covering batch and real-time ingestion, ETL/ELT transformation, cloud storage, orchestration, and data serving across AWS, Azure, and GCP.
Architect cloud data platforms — data lakes, lakehouses (Delta Lake, Apache Iceberg), and data warehouses (Snowflake, BigQuery, Azure Synapse, Amazon Redshift) — aligned to client scale and governance requirements.
Design real-time, event-driven, and AI/ML integration pipelines using Kafka, Kinesis, Event Hubs, and orchestration tools such as Airflow, LangGraph, and n8n.
Architect MLOps workflows including experiment tracking, model registry, automated retraining, and model monitoring using MLflow, Kubeflow, SageMaker Pipelines, or Azure ML.
Establish data governance frameworks covering data quality, lineage, cataloguing, and access control using Microsoft Purview, AWS Glue Data Catalog, or Apache Atlas.
Lead technical discovery workshops with clients, translating business requirements into solution designs, data models, and implementation roadmaps.
Support pre-sales by contributing to RFP responses, solution proposals, and client architecture presentations.
Team management, review engineering team designs to ensure adherence to architectural standards, security, and governance best practices.
Produce and maintain architecture documentation including solution designs, data flow diagrams, and technical decision records.
Qualifications:
B.Sc. or M.Sc. in Computer Science, Software Engineering, Data Science, or a related field.
6–9 years of experience across data engineering and AI/ML, with at least 2–3 years in an architect or principal engineer capacity.
Deep expertise in cloud data platform design on AWS, Azure, and/or GCP — including data lake, lakehouse, and data warehouse architectures at enterprise scale.
Hands-on experience with cloud-native data and AI services — AWS Glue, Redshift, SageMaker; Azure Data Factory, Synapse Analytics, Azure ML; BigQuery and Vertex AI.
Proven experience building ETL/ELT pipelines using Apache Spark and dbt, with strong SQL skills and familiarity with data modelling patterns (star schema, data vault 2.0, OBT).
Experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face) and MLOps tooling (MLflow, Kubeflow, SageMaker Pipelines).
Solid understanding of lakehouse formats (Delta Lake, Apache Iceberg) and workflow orchestration platforms (Apache Airflow, Prefect, Dagster).
Practical knowledge of data governance tooling for cataloguing, lineage, and quality management (Purview, Collibra, Apache Atlas).
Experience with containerisation (Docker, Kubernetes) and infrastructure-as-code (Terraform, CloudFormation).
Strong RFP contribution experience with clear technical writing and client-facing communication skills across technical and executive levels.
KPIs:
Architect and deliver at least three end-to-end Data & AI solutions per cycle meeting client requirements and quality standards.
Measurable contribution to pre-sales proposal win rate through strong technical positioning and solution design.
Maintain a reusable library of data and AI architecture patterns and reference designs that accelerate team delivery.
Zero critical architectural rework on delivered solutions through rigorous design review processes.
Strong client satisfaction scores on solution fit, platform reliability, and architecture quality across all engagements.
At NCINGA, you won’t just be designing systems; you’ll be the master architect of the intelligence that drives the modern enterprise. As an Architect – AI & Data, you’ll work at the high-stakes intersection of pre-sales and delivery, owning the blueprints for scalable data platforms and cutting-edge machine learning ecosystems. This is your opportunity to lead complex technical discoveries, design sophisticated MLOps workflows, and implement high-governance data lakehouses across a global cloud landscape.
Apply now and be the visionary force behind NCINGA’s most ambitious AI and data transformations!
