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About the Role

As AVP, Data Product Analyst, you will shape LPL’s strategic data foundation by connecting Business product owners with Technology delivery teams using data to power applications and experiences for our Advisors and Investors. You will be accountable for multiple domains of data that power products including Advisor and Investor platforms, performance reporting, supervision, account lifecycle management, billing, compensation, trading, money movement, proposal generation, CRM, BI reporting and institutional data distribution.

Responsibilities

Author operational and analytical data quality rules for respective data and business domains.
Document rules and partner with technology teams and engineers to have rules built into data pipelines, APIs, and a commercial tool quality framework.
Develop data profiling, quality, and alerting capabilities leveraging database and ETL capabilities (DBT, Airflow, SQL, etc.) or commercial data management tools (Collibra, Alation, atlan, AWS Datazone, data.world, etc.).
Develop and document standardized processes and workflows for remediating data issues by working with Relationship Management, Servicing, and Operations teams.
Assist with data issue research, impact analysis, and fixes by partnering with support and technology teams.
Translate business product, application, and capability requirements for Advisors and Investors into data needs and solutions, including business logic and transformations specs for data pipelines, inputs and business context for data modeling, and logic embedded in consuming APIs.
Utilize homegrown solutions, commercial data governance tools, or Excel to build and document data lineage views of data transformations across data ecosystems from source to target.
Maintain data lineage artifacts and leverage them for data research and remediation efforts.
Work with enterprise data architects to document data flows in conceptual and reference architecture diagrams for accountable data and business domains.
Use commercial governance tools or manually capture, document, and maintain data dictionaries at the attribute level for accountable domains.
Partner with the enterprise data modelling team to ensure consistency of data definitions, classifications, taxonomies, hierarchies, etc. across data assets and consuming applications.
Work with data product peers to identify inconsistencies in data to standardize on data definitions, code sets, naming conventions, classifications, consumption contracts, and taxonomies.
Define and configure workflows, metadata structures, data quality rules, and classification schemes based on defined requirements.
Author and enter Feature and Story-level work in Jira for technology teams to execute against.
Work with data domain teams and the enterprise modeling team to understand domain-level data models and the enterprise data model to determine if fit for purpose for new project intake or if changes are required for the data domain.
Provide scope and level of complexity if development work is needed.
Document drift and gaps between the enterprise logical data model and domain-level physical data models.
Represent data and participate in QE and end-to-end testing of data products.
Populate and enrich the business glossary or data dictionary and support and resolve data quality issues.
Leverage software, applications, and tooling to construct, monitor, govern, and maintain new data products for the company.
Manage data sharing and data delivery agreements as defined by the Data Design Authority, business stakeholders, data modeling, and engineering teams.
Partner with engineering for implementation and execution of data quality and privacy rules.
Ensure alignment of data schemas, models, contracts, and templates from ingestion to the enterprise data model to systems of record domains to consumption layers.
Align and govern physical models to logical data models.
Partner with the Risk organization for data archiving, retention, privacy, and data destruction policies and requirements for critical data elements.
Manage business metadata across accountable data domains and data products.
Onboard, govern, and certify new CDEs introduced into the data ecosystem.
Perform technical traceability mapping and data lineage tracking.
Validate and certify new data sources.
Partner with data domain (SOR) teams and business stakeholders to author and implement data quality rules and standards.
Provide operational oversight of data quality rules execution in partnership with Engineering and Operations.
Partner with internal support and Operations teams to build data quality scorecards, data exception reports, and assist teams with data enrichment and remediation.
Track data issues and risks and develop associated mitigation strategies for corresponding business domains.
Update central metadata repository with business metadata content including business terms, definitions, classifications, and data quality rules.

Requirements

Minimum of 7 years’ experience in data warehouse design, data management, data governance, business intelligence and analytics, or similar.
Minimum of 7 years and expert level use of reading and coding in SQL.
Minimum of 5 years’ experience with business intelligence tools and report development in tools like Tableau, Microsoft PowerBI, Domo, Qlik, Sisense, etc.
Experience in individual contributor-level data management roles like data analyst, data modeler, data pipeline engineer, BI analyst, or developer.
Knowledge base of data governance including data quality rules coding and implementation, data catalogs, quality scorecard development, data lineage, mastering data, and reference data management.
Experience using (data steward) or implementing (technology) data governance tools like Collibra, AWS Datazone, Alation, atlan, data.world, etc.
Hands-on data analysis, source-to-target mapping, data lineage tracing, remediation, etc.
Experience coding or reading and understanding data transformations in pipelines.
Experience designing and implementing a variety of data architecture patterns.
Experience using and developing in a variety of RDBMS like AWS, Databricks, Snowflake, Redshift, etc.
Wealth management and wealth advisory services industry experience.
Prior people leadership experience.
Prior experience in a data product management role.
Agile and lean delivery methods and associated tools like Confluence, Jira, etc.
Solid understanding of relational, star, snowflake data modeling.

Skills

SQL
Tableau
Microsoft PowerBI
Domo
Qlik
Sisense
Collibra
AWS Datazone
Alation
atlan
data.world
DBT
Airflow
AWS
Databricks
Snowflake
Redshift
Confluence
Jira

Location

Remote

Work Type

Full-time

Experience Level

Associate Vice President
7+ years
5+ years

Salary/Compensations

$103,309.00 - $172,113.00

Benefits

401K matching
health benefits
employee stock options
paid time off
volunteer time off

About the Company

LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S.
As a leader in the financial advisor-mediated marketplace, LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans.
The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses.
At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business.
They have the flexibility to do business their way.
And they have the freedom to manage their client relationships, because they know their clients best.
Simply put, we take care of our advisors and institutions, so they can take care of their clients.
LPL Financial is the nation’s largest independent broker-dealer.
Our company is widely known for its financial strength, exceptional service, and favorable industry reputation among financial professionals.
Financial guidance is a fundamental need for everyone.
LPL Financial creates the space to let you do what you do best – create personal, long-term client relationships that turn financial aspirations into realities.
Each year, thousands of financial professionals successfully manage billions of dollars in assets.
Because our company is not too big and not too small, you can seize the opportunity to make a real impact.

Equal Opportunity

Principals only.
EOE.