Job
Core
Design, evolve, and manage enterprise data architecture for real-time financial data streams, Data Lakes, and AI/ML infrastructure.
Role type
Senior Data Architect (Enterprise Data Strategy & Infrastructure)
Builds
Enterprise data architecture, real-time streaming pipelines, Data Lakes/Lakehouses, and AI-ready infrastructure.
Domain
Financial Technology / Real-time Data Engineering
Deliverable
production ML models | infrastructure
Required skills
Enterprise data architecture design, real-time streaming pipelines, Data Lake/Lakehouse management, SQL, Data Warehousing, Change Data Capture, streaming platforms, data processing tools, AI/ML ecosystem experience, Data Governance, Data Quality monitoring, Infrastructure as Code.
Preferred skills
Experience with geo-distributed architectures, petabyte-scale data handling, mentoring engineering teams.
Technologies
Kafka, Kinesis, Pub/Sub, Spark, Flink, dbt, Docker, Kubernetes, Terraform, CI/CD, Redshift, BigQuery, Snowflake, Azure Synapse, SageMaker, Vertex AI, MLflow, PostgreSQL.
Responsibilities
Design and evolve corporate data architecture including real-time streaming pipelines and Data Lakes; Facilitate Architecture Review Boards to establish data standards and best practices; Develop Architecture Decision Records covering data tiering, retention, and quality metrics; Build Data Lineage and centralized data ownership processes; Define and monitor SLA/SLO for data-related metrics; Make technological choices for data storage balancing functional requirements with cost; Formulate long-term data strategies for AI/ML adoption; Mentor data engineers and analysts.
Seniority
Senior, strategic leadership with hands-on architectural design
