Job description

Description: Why Join Smiley? Smiley Technologies offers the opportunity to be part of a company with a rich history and a commitment to innovation for core banking solutions. Founded in 2002, the company builds upon a legacy that began over 50 years ago with Systematic Inc., a pioneer in outsourcing data processing for banks. At Smiley Technologies, we prioritize a people-first culture, fostering a collaborative and optimistic work environment where respect and teamwork are paramount. Our dedication to exceptional customer service and continuous innovation makes us a trusted partner for community banks nationwide. By joining our team, you'll contribute to delivering advanced, reliable, and efficient technology stacks for Smiley and our client banks, making a meaningful impact in the financial industry. Requirements: The Director of Analytics is responsible for shaping and executing the company’s data and analytics strategy. This role leads the analytics team, oversees architecture and delivery of the modern data platform, and ensures secure, compliant, and high-value use of data in a banking and financial services context. The Director balances strategic vision, technical leadership, organizational management, driving adoption and customer value. This leader is accountable for ensuring the analytics platform delivers actionable insights, powers operational efficiency, supports regulatory compliance, and enables innovation for customers and internal stakeholders. Responsibilities Strategic Leadership • Define and own the enterprise analytics strategy, ensuring alignment with company goals, regulatory requirements, and customer needs. • Translate corporate strategy into a roadmap for data engineering, reporting/BI, advanced analytics, and AI/ML enablement. • Advocate for the value of analytics, securing buy-in and resources. • Represent analytics in cross-functional leadership forums, influencing technology and business direction. Organizational Leadership • Lead, mentor, and develop Team (Data Engineering, BI, Data Science enablement, Governance). • Establish a culture of excellence, accountability, and continuous learning, with focus on delivery, quality, and professional growth. • Manage hiring, retention, and performance of analytics staff. • Own and manage the analytics budget across staff, software tools, and cloud services, ensuring expense aligns with business priorities. • Partner with Finance to ensure budget adherence, vendor contract negotiations, and transparent reporting of spend vs. value delivered. • Forecast and track costs for Azure Databricks clusters, Azure Data Factory pipelines, storage, and Power BI licensing, optimizing for both performance and cost efficiency. Architecture & Platform Ownership • Oversee the design and evolution of the modern data Lakehouse platform using Azure Data Factory, Azure Databricks (Python, SQL), dbt (SQL, Jinja), Power BI, and related services. • Drive adoption of medallion architecture (bronze/silver/gold) and ensure strong integration across OLAP and OLTP systems. • Architect and enforce patterns for both data modeling (Kimball dimensional design for OLAP) and transactional design (SQL Server, DB2 for OLTP). • Guide platform automation, scalability, and repeatability using Terraform for infrastructure as code (IaC). • Ensure integration of advanced governance frameworks such as Unity Catalog and Microsoft Purview for lineage, security, and access control. Delivery & Execution • Ensure effective planning, prioritization, and delivery of analytics initiatives. • Drive adoption of Agile methodologies, ensuring that sprints deliver measurable business outcomes. • Define and enforce engineering best practices, including Git/GitHub workflows, CI/CD pipelines, peer review, and automated testing. • Oversee delivery of analytics products for both internal stakeholders and external clients, ensuring timeliness and precision. Security & Compliance • Ensure all analytics solutions adhere to banking and financial industry regulations. • Safeguard Sensitive Personally Identifiable Information (SPII) and ensure compliance with PCI DSS and SOC reporting standards. • Establish strong data governance and stewardship practices across OLAP, OLTP, and unstructured datasets. • Act as the accountable executive for data security and privacy incidents within analytics. • Other duties as assigned Required Education and Experience for Director Level • Bachelor of Science Degree in Computer Science or a related technical discipline, or equivalent experience • 8+ years of progressive experience in data engineering, analytics, or data platform leadership roles Smiley wants to encourage applications and will consider hiring this role at a Team Lead or Senior level if someone does not meet the qualifications for the Director-level. The Team Lead, Advanced Data & Analytics Architect plays a pivotal role in shaping and executing the company’s data and analytics strategy and is responsible for the design, implementation, and support of transactional and dimensional data warehouse development efforts. This role manages the analytics team, oversees architecture and delivery of the modern data platform, and ensures secure, compliant, and high-value use of data in a banking and financial services context. The Team Lead balances technical leadership, organizational management, driving adoption and customer value. This leader is accountable for ensuring the analytics platform delivers actionable insights, powers operational efficiency, supports regulatory compliance, and enables innovation for customers and internal stakeholders. Required Education and Experience for Team Lead Level • Bachelor of Science Degree in Computer Science or a related technical discipline, or equivalent experience • 5+ years of progressive experience in data engineering, analytics, or data platform leadership roles Required Knowledge, Skills, and Abilities for Director and Team Lead Levels • Deep expertise with Azure Databricks (Python, SQL, Delta Lake, streaming, Delta Live Tables) and Azure Data Factory • Proficiency with dbt (SQL, Jinja) and Power BI for transformation and visualization • Strong background in data modeling: • OLAP (Kimball dimensional modeling) for data warehouses • OLTP (SQL Server, DB2) for transactional systems • Experience with Git/GitHub workflows, CI/CD automation, and Terraform (IaC). • Proven experience in governing and securing data (SPII, PCI DSS, SOC, GDPR) in financial or regulated industries. • Strong executive communication skills, with ability to translate analytics into business value • Track record of strategic platform modernization and organizational scaling • Experience in creating reports and dashboards in PowerBI • Expert experience with MS SQL Server and SSIS • Ability to capture and transform business requirements into functional and data specifications • High level of initiative, self-starter, flexible, proactive, and a team player • Deep understanding of data marts, data warehouse architecture, multidimensional databases, data lakes, and data migration • Mainframe and DB2 experience a plus • Linux/Unix experience a plus • Strong technical aptitude and professional maturity • Expert with ITIL, Agile, SDLC, and DevOps as a methodology • Willingness to be On-Call • DevOps Mindset, Infrastructure as Code, and Data Ops for the data warehouse • Prepare the analytics platform for AI/ML workloads, predictive analytics, and real-time decisioning. • Drive enterprise readiness for secure data sharing and partner integrations. • Stay at the forefront of industry trends (open table formats, real-time analytics, AI copilots, regulatory tech) and translate them into organizational advantage. • Position analytics as a strategic differentiator for customer experience, operational excellence, and regulatory strength. What technologies will you get the opportunity to work with? • Azure Data Factory (required) • Azure Databricks (required) • DBT (SQL, Jinja) (required) • Python (required) • Prefect (knowledge of) • PowerBI (knowledge of) • Terraform (knowledge of) • SSIS (knowledge of) • Microsoft SQL Server (required) • DB2 (knowledge of)

Requirements