Director, Business Intelligence, Data Engineering

Darum lohnt es sich

Responsibilities • Build the Firm's Data Foundation • Design and implement a modern data warehouse or data lakehouse architecture from the ground up. • Evaluate and select the best-fit technologies, platforms, and tools based on organizational needs—not vendor preference. • Build scalable data pipelines that connect critical business systems including Salesforce/Litify, telephony platforms, financial applications, HR systems, and third-party SaaS solutions. • Establish automated, repeatable ETL/ELT processes that improve efficiency, reliability, and scalability. • Lead Data Strategy and Governance. • Create and implement a comprehensive data governance framework, including KPI definitions, metric standards, data dictionaries, and ownership models. • Establish data quality standards and processes that identify, measure, and remediate data integrity issues across the organization. • Drive consistency and trust in reporting by creating a single source of truth for business metrics and operational reporting. • Develop practices that ensure compliance with privacy, security, and regulatory requirements. • Transform Reporting into actionable intelligence. • Design and deliver executive dashboards and operational reporting that drive decisions—not just display information. • Partner with business leaders to translate strategic questions into meaningful metrics, analytics, and reporting solutions. • Build proactive analytics capabilities that identify trends, risks, opportunities, and performance drivers before stakeholders ask. • Elevate the organization from reactive reporting to predictive and insight-driven decision-making. • Lead and develop high-performing teams. • Lead a combined Business Intelligence and Data Engineering organization. • Hire, mentor, and develop technical talent while fostering a culture of accountability, innovation, and continuous improvement. • Establish team goals, roadmaps, and measurable quarterly outcomes aligned with business priorities. • Reduce operational risk by building scalable processes and eliminating single points of failure. • Partner across the business. • Collaborate with executive leadership, department leaders, and technology stakeholders to align data strategy with firm objectives. • Work closely with the VP of IT/CIO and peer technology leaders to ensure data architecture aligns with broader technology initiatives. • Serve as a trusted advisor who can translate complex technical concepts into clear, business-focused recommendations and insights.

Requirements • Bachelor's degree in Computer Science, Data Engineering, Information Systems, Statistics, or a related field. • 10–15 years of progressive experience in Data Engineering, Business Intelligence, Analytics, or related disciplines. • 7+ years of leadership experience managing technical teams and driving large-scale data initiatives. • Proven experience designing and building a data warehouse or data lakehouse—not simply managing an existing environment. • Strong expertise in SQL and at least one data engineering programming language (Python preferred). • Experience with cloud-based data platforms such as Azure, AWS, GCP, Snowflake, Databricks, or comparable technologies. • Strong understanding of data governance, data quality management, metadata management, and enterprise reporting. • Exceptional ability to communicate complex technical concepts to executive and non-technical audiences.

Proven ability to lead technical teams and drive data strategy aligned with business objectives. Core Competencies Demonstrates expertise in building data architectures, including data warehouses and lakehouses, while ensuring data governance and quality.