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Manager Data Analytics Engineer Jobs in Nottingham, MD

Senior Manager, Data Engineering - Remote Towson, MD USA Come make the world and accelerate your success. It takes great people to achieve greatness. People with a sense of purpose and integrity.

Data Strategy-Manager

Baltimore, MD · On-site

$99K - $232K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

Jr Data Engineer

Baltimore, MD · On-site

$30 - $40/hr

Working closely with senior engineers and analysts, you will help manage data infrastructure, build robust data workflows, and enable business intelligence initiatives. This is an excellent ...

Data Governance- Manager

Baltimore, MD · On-site

$99K - $232K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

Data Engineer

Hanover, MD · On-site

$112K - $135K/yr

Build data analytics solutions using Azure Synapse serverless SQL pools. * Perform data engineering ... Experience with Microsoft DevOps, or GitHub code management environment. * Experience or ...

Data Engineer

Hanover, MD · On-site

$113K - $136K/yr

Build data analytics solutions using Azure Synapse serverless SQL pools. * Perform data engineering ... Experience with Microsoft DevOps, or GitHub code management environment. * Experience or ...

Showing results 41-60

Manager Data Analytics Engineer information

See Nottingham, MD salary details

$44.3K

$129.1K

$176.7K

How much do manager data analytics engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for manager data analytics engineer in Nottingham, MD is $129,104.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $136,800.00 per year, depending on experience, location, and employer.

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 job categories do people searching Manager Data Analytics Engineer jobs in Nottingham, MD look for?

The top searched job categories for Manager Data Analytics Engineer jobs in Nottingham, MD are:

What cities near Nottingham, MD are hiring for Manager Data Analytics Engineer jobs?

Cities near Nottingham, MD with the most Manager Data Analytics Engineer job openings:

Infographic showing various Manager Data Analytics Engineer job openings in Nottingham, MD as of July 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $129,104 per year, or $62.1 per hour.

Data Scientist / Data Analytics Scientist (VIG-DS-01.080626)

Capital Solutions Group

Fort George G Meade, MD • On-site

Full-time

Posted 13 days ago


Job description

SECURITY CLEARANCE: T S/SCI with both Polygraphs is required
POSITION:  Data Scientist     (multiple LCAT levels cited below)
REQUISITION:  VIG-DS-01.080626
LOCATION:  Ft. Meade, Maryland

JOB DESCRIPTION: 
Use data, statistical/mathematical / computer science, reasoning, programming, and knowledge of the business or mission area to reach defensible conclusions.  Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in customer-base subset data holdings. 

Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. 

Effectively communicate complex technical information to non-technical audiences. 

Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly-shifting customer-bases collection, processing, storage and analytic capabilities and limitations.

REQUIRED
Employ some combination (2 or more) of the following skill areas:
1. Foundations: (Mathematical, Computational, Statistical) 
2. Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility)
3. Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)
(U//FOUO) Devise strategies for extracting meaning and value from large datasets. 


LCAT QUALIFICATIONS: 

CERTIFICATION:  n/a

EDUCATION + EXPERIENCE LEVEL

Data Scientist, Level 2
• Bachelor’s degree + 3 years relevant experience, OR
• Associates Degree + 5 years relevant experience


Data Scientist, Level 3
• Bachelor’s degree + 10 years of relevant experience, OR
• Associates Degree + 12 years relevant experience


Data Scientist, Level 4
• Bachelor’s degree + 15 years of relevant experience, OR
• Associates Degree + 17 years relevant experience

CSG, Inc. is an Equal Opportunity / Affirmative Action employer that values the strength of diversity in the workplace. All qualified applicants will receive consideration for employment without discrimination or harassment based on race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital or domestic/civil partnership status, genetic information, citizenship status, veteran status, or any other characteristic protected by law.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.