Data Solutions Architect (Financial Services)

📋 Description

• • Architect and deliver end-to-end data solutions that power critical decision-making for the world’s largest banks, insurers, and asset managers. You will design lakehouse platforms on Databricks that unify structured trading data, unstructured customer communications, and real-time market feeds into a single source of truth capable of sub-second analytics at petabyte scale.
• • Serve as the primary technical authority during pre-sales pursuits, translating vague RFP requirements into crisp solution visions. You will run white-boarding sessions with C-level stakeholders, build rapid prototypes in Databricks SQL and PySpark, and quantify ROI models that demonstrate how a modern lakehouse can reduce total cost of ownership by 40 % while accelerating regulatory-reporting cycles from weeks to hours.
• • Own the full delivery lifecycle—from initial discovery workshops through production cut-over—ensuring every architecture decision meets banking-grade security, compliance, and performance standards. You will map business capabilities to medallion-architecture zones (Bronze, Silver, Gold), define streaming ingestion patterns using Delta Live Tables, and implement Unity Catalog governance policies that satisfy Basel III, CCAR, and GDPR mandates without stifling self-service analytics.
• • Lead cross-functional teams of 5–10 data engineers, data scientists, and cloud architects spread across North America, EMEA, and APAC. Provide hands-on mentorship in Spark performance tuning, Delta Lake optimization, and MLOps automation using MLflow; maintain burndown charts, risk registers, and client-satisfaction KPIs that keep multi-million-dollar programs on track and on budget.
• • Continuously optimize mission-critical workloads that process over 50 TB of transactions, market data, and reference data daily. You will refactor legacy ETL pipelines into streaming Delta pipelines, reduce batch windows from 6 hours to 15 minutes, and eliminate Kafka lag spikes during market-open surges—directly impacting trading desk P&L and regulatory-reporting deadlines.
• • Establish enterprise data-governance guardrails that allow business analysts to explore sensitive datasets without compromising privacy or audit trails. Define data-quality SLAs, lineage policies, and role-based access controls that satisfy both internal risk committees and external regulators, while enabling self-service analytics adoption to grow from 20 % to 80 % of the user base within 12 months.
• • Evaluate and integrate emerging technologies—Apache Iceberg, Snowflake native apps, Lakehouse Federation, real-time feature stores—through internal POCs and reference architectures. Package reusable accelerators (Terraform modules, dbt macros, MLflow project templates) that shorten future project ramp-up by 30 % and reinforce SunnyData’s reputation as the premier Databricks partner in financial services.
• • Translate complex technical achievements into board-ready narratives. Build executive dashboards in Databricks SQL and Tableau that visualize data-platform ROI, cost-to-serve trends, and predictive capacity-planning metrics, guiding multi-year investment decisions and securing follow-on expansions worth $2–$5 M annually.
• • Champion a culture of experimentation and continuous learning by running weekly architecture guilds, lunch-and-learn sessions, and quarterly hackathons. Publish best-practice blogs, speak at industry conferences, and mentor junior consultants—elevating the entire firm’s technical bar and ensuring SunnyData remains two steps ahead of market demand.