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Sterling Capital Management LLC Linkedin · Posted 5d ago

Senior Investment Data Analyst

Charlotte

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Company Statement

Sterling Capital Management LLC (SCM), founded in 1970, is an indirect, wholly-owned subsidiary of Guardian Capital Group Limited. Headquartered in Charlotte, SCM provides investment advisory services through mutual funds, separately managed accounts, model portfolios, and other commingled vehicles offered through a variety of intermediary and managed account platforms. SCM’s five distinct investment teams provide a full complement of fixed income, active equity, and multi-asset solutions.


Job Statement

Sterling Capital Management is seeking a Senior Investment Data Analyst to join our Enterprise Data Management team. This role sits at the intersection of investments, data, and technology and is responsible for ensuring that critical investment data is accurate, trusted, and effectively integrated across the firm's investment ecosystem.


This is a hands-on role that combines investment data expertise with data analysis, problem solving, automation, and modern data technologies. The successful candidate will develop a deep understanding of how data moves across Sterling's investment platforms, investigate complex data issues, identify root causes, and implement sustainable solutions.

The role will have significant responsibility for Sterling's investment security and reference data while also serving as a hands-on contributor to the continued development of our enterprise data warehouse and modern data platform.


Essential Duties and Responsibilities

  • Develop deep expertise in Sterling's investment data, including securities, benchmarks, pricing, credit ratings, classifications, and other reference and market data.
  • Support critical investment data across portfolio management, trading, accounting, compliance, performance, and other enterprise platforms.
  • Investigate complex data issues using SQL and other analytical tools, tracing data across source systems, integrations, transformations, and downstream applications to identify root causes.
  • Research and analyze equity and fixed-income securities using market and reference data providers including Bloomberg, FactSet, ICE, and rating agencies.
  • Identify recurring issues and control gaps and implement sustainable solutions through improved processes, automation, and technology.
  • Partner directly with Portfolio Management, Trading, Compliance, Performance, Investment Operations, and Technology to understand and solve business and data challenges.

Data Warehouse & Modern Data Platform

  • Serve as a hands-on contributor to the design, development, testing, and ongoing evolution of Sterling's enterprise data warehouse.
  • Partner with Data Engineering and business stakeholders to translate investment data requirements into scalable data models, transformations, and data solutions.
  • Contribute data transformations, business rules, data-quality tests, reconciliations, and validation processes using SQL and modern data development tools.
  • Participate directly in developing and operationalizing data pipelines and workflows using technologies such as Snowflake, dbt, Dagster, Python, and related cloud data tools.
  • Help establish trusted, reusable investment data sets for operational, investment, reporting, analytical, and technology use cases.
  • Contribute to data modeling, documentation, lineage, testing, and governance as Sterling's modern data platform continues to evolve.

Data Solutions & Continuous Improvement

  • Design and enhance data flows, integrations, controls, and automated workflows across Sterling's investment technology environment.
  • Translate business needs into clear data and technical requirements and partner with technology teams through implementation.
  • Lead or contribute to cross-functional data initiatives, system enhancements, integrations, and process improvements.
  • Partner with external data and technology vendors to investigate issues and improve end-to-end data processes.
  • Contribute to enterprise data management practices including data quality, data definitions, lineage, master data management, and data governance.


Required Qualifications:

  • Highly self-motivated with a strong work ethic and a willingness to take initiative, step into challenges, and contribute wherever needed to help the team succeed.
  • Bachelor's degree in Finance, Computer Science, Information Systems, Data Analytics, or a related field, or equivalent professional experience.
  • 5+ years of relevant experience in asset management, investment data, financial services, or a related data or technology function.
  • Strong understanding of financial markets and investment securities, including equity and fixed-income instruments.
  • Experience working with investment, security master, reference, market, pricing, or portfolio data.
  • Strong SQL skills with the ability to independently analyze data, troubleshoot issues, and perform root-cause analysis.
  • Experience working with data integrations, transformations, mappings, and workflows across multiple systems.
  • Strong analytical and problem-solving skills with the ability to independently investigate complex issues and drive them through resolution.
  • Strong communication skills with the ability to work effectively across both business and technology teams.
  • Demonstrated ability to take ownership, manage competing priorities, and drive projects and initiatives through completion.


Preferred Qualifications:

  • Asset management experience strongly preferred.
  • Experience with Charles River Investment Management System (CRD/CRIMS), Advent APX, or similar investment management platforms.
  • Experience with market and reference data providers such as Bloomberg, FactSet, ICE, Fitch, Moody's, or S&P.
  • Hands-on experience with a modern data warehouse or cloud data platform, including data transformation, modeling, testing, or data-quality processes.
  • Experience with Snowflake and dbt strongly preferred.
  • Experience with Dagster, Airflow, or another modern data orchestration platform is a plus.


Compensation:

  • Commensurate with experience
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