Filtr uses AI to scan 1000+ jobs and finds postings that perfectly matches your resume

LPL Financial is seeking a VPII of the Data Analytics Engineering to lead the strategic vision and execution of data initiatives across the organization, ensuring alignment with business objectives and driving data-driven decision-making to unlock business value and competitive advantage.

Requirements

• 15+ years of experience in data engineering, architecture, governance and advanced analytics consumption, with at least 5 years in a senior leadership role.
• Proven track record of leading large-scale data enterprise data transformation programs with clearly articulated results.
• Deep expertise in data engineering and automation, governance frameworks, data privacy, and data compliance standards.
• Experience leading advanced data and full stack engineering teams.
• Experience with technical implementation of data cataloging, data quality assurance, observability and metadata management tooling.
• Data product and data mesh/fabric architecture experience preferred.
• AWS, Snowflake, dbt and API gateway and development experience preferred.

Responsibilities

• Develop and implement the overall data strategy, ensuring alignment with business objectives and driving data-driven decision-making across the organization.
• Oversee the design and delivery of modern, scalable data architectures that support advanced analytics, AI, and digital transformation initiatives.
• Partner with warehousing teams to establish security-focused, quality assured data product and data contract engineering standards for the management and rapid expansion of data products for consumption by AI and ML modeling teams, downstream consumers and BI layers.
• Lead a team of high-performing engineers and analysts to evaluate, resolve, decommission and/or modernize legacy data solutions and applications, applying industry best practices and automation to expedite transformation.
• Integrate data security, compliance, and governance policies, architectures and best practices across data analytics solutions to ensure we exceed regulatory and organizational standards.
• Establish and maintain robust metadata management automation solutions within the data analytics ecosystem; advancing upstream and downstream integration to enterprise tooling to ensure data quality and accessibility.
• Partner with the AI engineering team to ensure the establishment of automation for maintenance, integration and CICD standards for AI-ready data pipelines to support advanced analytics and machine learning initiatives.

Other

• Bachelor’s degree in Data Science, Computer Science, or a related field; Master’s degree preferred.
• Exceptional and proven leadership capabilities, including development of advanced analytic engineering teams.
• Outstanding communication and stakeholder engagement skills, with the ability to influence at the C-suite and board levels.
• Excellent communication and stakeholder management skills. Strong business acumen is needed, and direct experience with business customers is required.
• Proven track record of establishing, developing and leading high-performing data engineering teams.