Senior Data Architect (Modernization & Cloud Platforms)

Mphasis; New York (NY); On-site; USD 130,000 - 150,000; Full time

Job summary

A technology company is seeking a visionary Senior Data Architect to lead an enterprise-wide data transformation in New York. This role entails designing a strategy for migrating legacy data infrastructures into modern cloud-native environments. Candidates should possess over 10 years in Data Architecture and expert-level proficiency in AWS, Azure, or GCP. Responsibilities include creating blueprints for ELT/ETL pipelines and optimizing data movement across hybrid clouds. Join us to innovate in data solutions.

Qualifications

• 10+ years in Data Architecture/Engineering; 5+ years leading large-scale cloud migrations.
• Expert-level proficiency in AWS (Lake Formation/Glue), Azure (Synapse/Fabric), or GCP (BigQuery/Dataflow).
• Strong understanding of legacy patterns and how to decouple them.

Responsibilities

• Design and execute the strategy to migrate from legacy RDBMS and mainframes to modern Data Lakehouses.
• Define the 'Modern Data Plane' architecture, ensuring seamless integration across environments.
• Create reusable 'Blueprints' for ELT/ETL pipelines and real-time streaming architectures.

Skills

Data Architecture

Cloud Migration

AWS

Azure

GCP

Data Mesh

Data Fabric

ELT/ETL Pipelines

Kafka

Job description

We are seeking a visionary Senior Data Architect to lead our enterprise-wide data transformation. You will be the primary architect responsible for the strategic migration of legacy data infrastructures into a modern, cloud-native data plane. This role requires a rare blend of deep engineering roots, enterprise architectural foresight, and innovation leadership to build data systems that are not just scalable, but "future-proof."

Key Responsibilities

Strategic Architecture & Migration

• Legacy-to-Modern Roadmap: Design and execute the multi-year strategy to migrate from legacy RDBMS and mainframes to modern Data Lakehouses and Data Meshes.
• Data Plane Evolution: Define the "Modern Data Plane" architecture, ensuring seamless integration between storage (S3/ADLS/GCS), compute (Spark/Snowflake/Databricks), and consumption layers.
• Hybrid Cloud Strategy: Architect robust patterns for data movement across hybrid and multi-cloud environments, ensuring minimal downtime and zero data loss.

Engineering Excellence & Implementation

• Pattern Development: Create reusable "Blueprints" for ELT/ETL pipelines, Change Data Capture (CDC), and real-time streaming architectures using Kafka or Redpanda.
• Performance Engineering: Optimize cloud spend and query performance by implementing advanced indexing, partitioning, and caching strategies.
• Automated Governance: Architect "Security-as-Code" within the data plane, integrating PII redaction, data masking, and RBAC directly into the automated deployment pipelines.
• AI/ML Readiness: Architect data planes specifically optimized for Generative AI and LLM workloads (e.g., Vector Databases, Feature Stores).
• Self-Service Innovation: Design and lead the implementation of a Data Catalog and self-service portal to empower data scientists and analysts.

Required Skills & Qualifications

Experience

10+ years in Data Architecture/Engineering; 5+ years leading large-scale cloud migrations.

Expert-level proficiency in AWS (Lake Formation/Glue), Azure (Synapse/Fabric), or GCP (BigQuery/Dataflow).

Legacy Systems

Strong understanding of legacy patterns (Netezza, Teradata, Oracle, Mainframe) and how to decouple them.

Modern Standards

Hands-on experience with Data Mesh, Data Fabric, and Open Table Formats (Iceberg, Delta Lake).

Certifications

Preferred: AWS Solutions Architect Pro, Google Professional Data Engineer, or CDMP.