Job Description:

The Director of Data Platforms is responsible for leading a function and/or collection of teams within CSI's data engineering organization in the design, delivery, and continuous improvement of secure, scalable, well-governed data platforms and pipelines across CSI's banking and fintech solutions. This position executes the data platform technology vision and organizational plans in conformance with the company's policies and the objectives of senior management, and is responsible for the workload, outputs, and resources within the data engineering function. The Director establishes short- and long-term goals, standards, and processes that align data platform delivery with broader product, analytics, and AI strategies, leads a team of engineering managers, and champions continuous improvement and strong governance across the data lifecycle.

Key Responsibilities

Leadership & Organizational Management

• Directs a department of data engineers, data architects, quality engineers, and other individual contributors to achieve strategic and operational goals for CSI's data platforms.
• Inspires, coaches, and provides guidance to team members to improve performance, drive accountability, and support achievement of business objectives.
• Partners with senior leadership on the data platform vision and strategy, helping shape the future-state data engineering organization.
• Communicates organizational priorities, policy, and strategy clearly across the department.
• Champions a culture of ownership, initiative, continuous improvement, and strong data stewardship.
• Upholds all policies and procedures, company culture, and values.

Data Platform Delivery & Engineering Oversight

• Owns the quality of data pipelines, warehouses, and platforms delivered, and the implementation of standards, methods, metrics, and procedures across the data engineering lifecycle, evaluating and refining as needed with other leaders in the organization.
• Directs the architecture, performance, and cost management of CSI's Snowflake environment, including warehouse sizing, workload management, and credit optimization.
• Drives a sense of urgency for platform and process improvement to meet and exceed internal and customer data requirements.
• Applies lean principles to reduce pipeline cycle time and eliminate waste across the data development process.
• Works with other leaders to standardize data engineering practices, including data modeling, pipeline testing, transformation standards (e.g., dbt), documentation, and reporting on overall platform performance.
• Reviews and approves data platform releases, schema changes, and deployment plans, ensuring delivery risk is appropriately identified and managed.
• Leads or supports root cause analysis on significant data quality incidents or pipeline failures in partnership with engineering teams and drives preventive action.

Data Governance, Classification & Audit

• Owns and matures CSI's data governance framework, including data classification standards (e.g., confidential, PII, non-public personal information), data lineage, cataloging, and retention practices.
• Serves as a primary point of contact for internal and external audit teams on matters related to data platform controls, access governance, and evidence collection.
• Partners with Compliance, Risk, and Legal to ensure data governance practices align with applicable regulatory requirements (e.g., GLBA, SOC 2, state privacy laws) and internal policy.
• Establishes and maintains audit trails, access reviews, and lineage documentation sufficient to support SOC 2 assessments, regulatory exams, and third-party audits.
• Implements and enforces role-based access control (RBAC) and least-privilege principles across Snowflake and other data platforms.
• Leads data quality monitoring, issue remediation, and metadata management programs to build organizational trust in reported data.

Operational Performance & Process Improvement

• Establishes and reviews reporting and dashboards that track departmental priorities, platform reliability, data quality, and goal achievement.
• Prepares and manages budgets for the data engineering department, including Snowflake and related platform spend, and monitors spend against plan.
• Leads or contributes to yearly budget and headcount planning for the organization.
• Ensures appropriate staffing levels, effective workload balance, and scalable data engineering practices across teams.
• Uses engineering and data metrics/KPIs (e.g., pipeline reliability, data quality, query performance, cost per workload) to measure team performance and drive targeted, continuous improvement actions.

Cross-Functional Partnership

• Works closely with product, analytics, data science/AI, and QA teams to define data platform requirements and data-related metrics.
• Partners with security, risk, and vendor management on due diligence, audit evidence, and response to RFP or security questionnaires as needed.
• Partners with internal and external audit teams on a recurring basis to support control testing, evidence requests, and remediation of findings.
• Partners with infrastructure and operations teams as required and appropriate on capacity planning, hosting, and platform reliability.
• Works effectively with all levels of leadership, including business and customer-facing stakeholders, to support delivery success.
• Stays current on industry trends, data engineering best practices, and the broader data/analytics stack to support team readiness and capability development.
• Partners with infrastructure and network teams to resolve technical integration challenges as acquired platforms and data sources are brought into CSI's broader data environment.

People Leadership

• Leads, mentors, and evaluates managers, including regular 1:1s, goal setting, coaching, and performance review processes.
• Participates in interviews and hiring decisions for data engineering leadership and key technical roles.
• Builds high-performing teams that demonstrate accountability, adaptability, and strong employee engagement.
• Demonstrates a track record of recruiting, developing, and retaining high-quality data engineering talent.

Governance, Risk & Compliance

• Oversees access control processes for data platforms and engineering systems, ensuring appropriate approvals and audit trails.
• Supports initiatives to reduce reliance on shared credentials and strengthen controls around production and data access.
• Partners with vendor management on contract review, vendor risk, and cost control for data platform vendors and tools (e.g., Snowflake, ELT/ETL tooling, data catalogs).
• Owns SOC 2 and other audit or compliance efforts as they relate to data platforms, ensuring timely and complete evidence collection from engineering teams.

Required Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent experience.
• 10+ years of relevant experience in data engineering or software engineering, including a strong technical background as an individual contributor on data platforms.
• Proven, hands-on experience with Snowflake required, including architecture, performance tuning, security model, and cost/credit management.
• Proven experience managing managers and leading multi-layered data engineering teams in a complex environment.
• Demonstrated expertise in data governance, data classification, and metadata management practices across large teams.
• Direct experience supporting internal and external audit engagements, including evidence collection, control testing, and remediation.
• Strong understanding of Agile methodologies.
• Demonstrated success recruiting, developing, and retaining high-quality data engineering teams.
• Excellent written and oral communication skills, with the ability to present technical and business information to a wide audience including auditors, customers, peers, and staff.
• Strong analytical, decision-making, and problem-solving skills; comfortable operating with ambiguity.

Preferred Qualifications

• Experience in banking, fintech, or financial services, including regulated data environments.
• Experience with the modern data stack (e.g., Snowflake, dbt, Airflow, Fivetran, or similar ELT/ETL and orchestration tools) and cloud platforms (AWS or Azure).
• Experience with data catalog and lineage tooling (e.g., Collibra, Alation, Atlan) and classification/tagging frameworks.
• Familiarity with regulatory and compliance frameworks relevant to banking data (e.g., GLBA, HMDA, SOC 2).
• Deep experience working with either Atlassian Jira or Azure DevOps to manage data engineering SDLC.
• Experience driving change across a complex, global engineering organization.
• Familiarity with vendor management and security or RFP response processes.

What Success Looks Like

• Engineering teams are well-prepared, supported, and consistently meet delivery expectations.
• Data platforms deliver secure, high-quality, well-governed data on predictable cadences with continually improving pipeline reliability.
• Data classification, lineage, and access governance are consistently applied across all data assets.
• Internal and external audits proceed smoothly, with evidence readily available and findings proactively remediated.
• The Snowflake environment is optimized for cost, performance, and security.
• Leadership has clear visibility into data platform priorities, progress, and performance through KPIs and dashboards.
• CSI's data engineering organization continues to evolve toward a stronger, more resilient, and well-governed data foundation.