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Data Analyst II

Envestnet

Description

Envestnet is seeking a Data Analyst II to join our Product department. This is a hybrid role, with in-office work required at our Berwyn, PA office location.

Envestnet is transforming the way financial advice is delivered through its connected technology, advanced insights, and asset management solutions – backed by industry-leading service and support. Since 1999, Envestnet has served the wealth management industry and today supports trillions in platform assets, serving over a hundred thousand financial advisors. The vast majority of the nation’s leading banks, the largest wealth management and brokerage firms, and over 500 of the largest RIAs rely on Envestnet’s wealth management platform and solutions to drive business growth, boost productivity, and deliver better financial outcomes for their clients. 

Envestnet’s Strategy:

  • Deliver the industry-leading wealth management platform, powered by advanced data and insights 

  • Leverage our scale and efficiencies to serve our clients’ needs comprehensively 

  • Enable financial advisors to deliver more holistic advice – reflecting a more complete view of their clients’ financial lives, and in a more connected environment

For more information, please visit

Job Summary: 

Envestnet is looking for a Data Analyst II to work our Product Team to achieve strategic objectives around data quality and enrichment. As a Data Analyst II, you will support the development of data-driven, analytical solutions related to our platform and perform effective evaluation of output quality against business targets.

Job Responsibilities:

  • Partner with stakeholders (Product, Data Science, Sales, Professional Services, and Client Services) in the delivery of analytics that will strengthen our data products and reduce client support requests.

  • Collaborate with Product Management, Data Science, and Engineering teams to define, scope, and develop new features & functionality geared towards the platform.

  • Perform Data Analysis, Joins, Aggregations and Sub Queries. 

  • Monitor platform performance and calculate accuracy metrics.

  • Provide clear, insightful interpretation of available internal and external data.

  • Use data to create models that depicts trends.

  • Perform data quality and accessibility testing and verification of data sets.

  • Interact with external clients on a weekly basis by providing timely and professional updates.

  • Adherence to and application of Envestnet legal, compliance, risk, business continuity and administrative policy within the role and department(s) including the timely completion of training & awareness, affirmations and testing as requested. 

  • As part of the responsibilities for this role, you will understand and readily support Envestnet's established corporate business practices, policies, internal controls and procedures designed to create value or minimize risk.

Required Qualifications: 

  • 3+ Years of experience in Data Analysis and/or Data Science

  • Strong SQL skills

  • Familiarity with DBT is a plus

  • Familiarity with, or the desire to learn Python for data analysis

  • Experience manipulating and analyzing large and complex data sets

  • Understanding of data quality (DQ) concepts and a familiarity with DQ tools/methods

  • Passion for working with data & a strong attention to detail

  • The ability to identify trends and patterns of information

  • An understanding of general landscape for data science and opportunities within AI

Envestnet: 

  • Be a member of an innovative and industry leading financial technology and solutions company 

  • Competitive Compensation/Total Reward Packages that include:

    • Health Benefits (Health/Dental/Vision)

    • Paid Time Off (PTO) & Volunteer Time Off (VTO)

    • 401K – Company Match

    • Annual Bonus Incentives

    • Parental Stipend 

    • Tuition Reimbursement

    • Student Debt Program

    • Charitable Match 

    • Wellness Program

Envestnet is an Equal Opportunity Employer.

#LI-AQ1

Vacancy posted 1 day ago
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