Data Architect at DS Technologies Inc in CA-San Francisco-94101

Job description

• DS Technologies Inc is looking for Data Architect role for one of our premier clients.

Responsibilities

• Primary focus: Data readiness, canonical standards, conceptual modelling, and gap analysis.
• • Lead the creation of the conceptual, logical, and physical data models.
• • Lead the Conceptual Data Model (CDM) development for entities relevant to client's models (Customer, Account, Transaction, Product).
• • Conduct data profiling and quality assessments of required model inputs.
• • Map current attributes to client's model feature requirements and identify gaps.’
• • Assess readiness of data domains (transaction history, merchant detail, behavioral metrics).
• • Review existing canonical data standards, metadata, and lineage to determine compatibility with modelling needs.
• • Define early-stage transformation and enrichment needs (behavioral features, aggregations, rolling windows).
• • Define and oversee the strategy for data ingestion, movement, and synchronization from Snowflake to Databricks.
• • Ensure schema consistency, data completeness, and performance for high-volume transactional datasets.
• • Partner with engineering and platform teams to ensure the data foundation meets model requirements.
• • Evaluate feasibility of creating model-ready datasets.

Requirements

• • 10+ years of PHP development experience, including API design and integration work.
• • Proven experience integrating with credit card processors or servicers (e.g., TSYS, Fiserv, etc.).
• • Strong understanding of banking systems and core banking integration patterns.
• • 7–10+ years of experience in data architecture, data platform engineering, or large-scale analytics systems.
• • Deep expertise with Databricks, PySpark/Spark, Delta Lake, and distributed compute architectures.
• • Strong knowledge of Snowflake, including data modelling, ingestion patterns, and performance scaling.
• • Hands-on experience designing data architectures to support ML workloads, feature engineering and model scoring.
• • Demonstrated ability to design end-to-end pipelines in complex, regulated data environments.
• • Strong understanding of Azure cloud platform, IAM, and enterprise security practices.
• • Excellent communication skills with ability to collaborate across engineering, data science, product, and governance teams.
• • Prior involvement in ML Ops architectures or model deployment frameworks.

Skills

Required

• PHP development
• API design and integration
• Data architecture
• Data platform engineering
• Large-scale analytics systems
• Databricks
• PySpark/Spark
• Delta Lake
• Distributed compute architectures
• Snowflake
• Data modelling
• Ingestion patterns

Preferred

• ML Ops architectures
• Model deployment frameworks

Benefits

• Compensation: $150,000.00 per year