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Manager Data Analytics Engineer Jobs in Delaware

Contribute to the continuous improvement of data quality and data management processes. The above ... Experience with SQL, Python, R, or other programming languages commonly used in analytics. * Strong ...

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Manager Data Analytics Engineer information

What is a manager data analytics engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.

How does a manager data analytics engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What are the key skills and qualifications needed to thrive as a manager data analytics engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

What are the most commonly searched types of Data Analytics Engineer jobs in Delaware?

The most popular types of Data Analytics Engineer jobs in Delaware are:

What are popular job titles related to Manager Data Analytics Engineer jobs in Delaware?

For Manager Data Analytics Engineer jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Manager Data Analytics Engineer jobs in Delaware look for?

The top searched job categories for Manager Data Analytics Engineer jobs in Delaware are:

What cities in Delaware are hiring for Manager Data Analytics Engineer jobs?

Cities in Delaware with the most Manager Data Analytics Engineer job openings:

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 days ago


OneMain Financial rating

7.4

Company rating: 7.4 out of 10

Based on 101 frontline employees who took The Breakroom Quiz

117th of 150 rated financial services


Job description

Manager, Data Science

Location: Wilmington, DE (Hybrid Schedule)

OneMain Financial is seeking a Data Science Manager based out of Wilmington, DE, to join our innovative and fast-moving Data Science team.

Successful candidates will be willing to challenge assumptions and bring fresh ideas, own projects from inception to production, and collaborate with internal partners to improve customer experience and drive OneMain's financial performance.

Example projects include building underwriting models for our core personal loans business; evaluating new data sources, technologies, and model-building techniques; and developing algorithmic solutions to automate income verification.

Key qualities include creativity, clarity in communication, ability to strike a balance between speed to market and quality of delivery, and a willingness to seek out or develop new tools and ideas. Bring your individual strengths, knowledge, and interests to bear on the problems we tackle. Propose new ideas. Pursue some of them.

Responsibilities:

  • Identify high impact opportunities where a model or data-related solution can provide large leverage. Then design, build, validate, implement, monitor, and improve that data science solution.
  • Identify new data sources, new technologies, new techniques, and new insights that will create value for our customers and lines of business.
  • Promote best practices for model development and software design.
  • Communicate and collaborate with cross-functional partners.
  • Work with third-party vendor partners to evaluate data and products and integrate those that that show promise into our data science practices and platforms.
  • Develop testing & control procedures to ensure execution accuracy and effective post-implementation monitoring.
  • Independently complete analyses, draw conclusions, and present results to influence business & strategy decisions.
  • Unlock insights from non-traditional data sources such as information from other industries, tax data, deposit data, demographic data, and digital data.

Requirements:

Technical skills
  • Proven experience with data analysis and coding equivalent to 4+ years of experience working as a data scientist
  • Applied experience with a variety of modeling techniques like regression, boosted decision trees, deep learning, NLP, and so forth
  • Strong software development skills covering design, algorithms, optimization, testing, and source control
  • Hands-on experience with building self-contained solutions with clear interfaces
  • Demonstrable mathematical and algorithmic aptitude
Communication
  • Outstanding communication skills with the comfort to interact with all levels with clarity and at an appropriate level of detail
  • Ability to identify and convey the essential information in every communication
  • Ability to understand the business intent behind every project and tell the story around it
  • Willingness to propose and defend ideas
Collaboration
  • Experience working in cross-functional teams across a large, multi-stakeholder organization
  • Ability to work with a high degree of autonomy: can resolve or escalate issues appropriately; can fill in the gaps when requirements are incomplete
  • Ability to work with teams of diverse individuals focused on several disparate projects simultaneously
Risk management mindset
  • Can foresee risks and potential points of failure in a data science system and appropriately mitigate or manage them
    • Anticipate weaknesses in models, software, and systems
    • Use defensive practices to build robust products (e.g. testing, code review)
    • Minimize surface area for failure (develop around clear interfaces, use well-understood tools, minimize external dependencies)
    • Prepare for the unexpected (fail fast with clear error messages, develop failure contingency plans)
    • Understand the importance of monitoring production systems and setting up clear alert systems
  • Appropriately balance the tradeoffs between the use of cutting-edge enterprise systems vs. simple and familiar tooling

Who We Are

OneMain Financial (NYSE: OMF) is the leader in offering nonprime customers responsible access to credit and is dedicated to improving the financial well-being of hardworking Americans. Since 1912, we've looked beyond credit scores to help people get the money they need today and reach their goals for tomorrow. Our growing suite of personal loans, credit cards and other products help people borrow better and work toward a brighter future.

Driven collaborators and innovators, our team thrives on transformative digital thinking, customer-first energy and flexible work arrangements that grow lives, careers and our company. At every level, we're committed to an inclusive culture, career development and impacting the communities where we live and work. Getting people to a better place has made us a better company for over a century. There's never been a better time to shine with OneMain.

Because team members at their best means OneMain at our best, we provide opportunities and benefits that make their health and careers a priority. That's why we've packed our comprehensive benefits package for full- and some part-timers with:

  • Health and wellbeing options including medical, prescription, dental, vision, hearing, accident, hospital indemnity, and life insurances

  • Up to 4% matching 401(k)

  • Employee Stock Purchase Plan (10% share discount)

  • Tuition reimbursement

  • Paid time off (15 days' vacation per year)

  • Paid sick leave as determined by state or local ordinance, prorated based on start date

  • Paid holidays (11 days per year, based on start date)

  • Paid volunteer time (3 days per year, prorated based on start date)

OneMain Holdings, Inc. is an Equal Employment Opportunity (EEO) employer. Qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship status, color, creed, culture, disability, ethnicity, gender, gender identity or expression, genetic information or history, marital status, military status, national origin, nationality, pregnancy, race, religion, sex, sexual orientation, socioeconomic status, transgender or on any other basis protected by law.


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