Data Analytics Engineer Jobs in South Carolina
Data Analytics Engineer jobs in South Carolina are concentrated in Charlotte-adjacent markets like Rock Hill, along with Columbia and Greenville, where employers such as BlueCross BlueShield of South Carolina, Michelin North America, and Sonoco Products maintain substantial analytics functions. Demand is strongest for engineers skilled in dbt, Snowflake, and cloud-based pipeline architecture, with openings at every level from associate data engineer to senior analytics lead. Find a role that fits below and apply directly.
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Location
Charleston - 997 Morrison Drive, Suite 402Business
Our Growth, Your Opportunity
At Maymont Homes, our success starts with people, our residents and our team. We are transforming the single-family rental experience through innovation, quality, and genuine care. With more than 20,000 homes across 47+ markets, 25+ build-to-rent communities, and continued expansion on the horizon, we are more than a leader in the industry—we are a company that puts people and communities at the heart of everything we do.
As part of Brookfield, Maymont Homes is growing quickly and making a lasting impact. We are also proud to be Certified™ by Great Place to Work®, a recognition based entirely on feedback from our employees. This honor reflects the culture of trust, collaboration, and belonging that makes Maymont a place where people thrive.
Join a purpose-driven team where your work creates opportunity, sparks innovation, and helps families across the country feel truly at home.
Job Description
Position Summary
The Director of Data Science and Strategic Analysis is responsible for independently scoping, executing, and delivering investment-grade research that translates complex demographic, macroeconomic, and market data into specific, actionable capital deployment opportunities. The research will then form the foundation for advanced data science models, analytics, and decision-support tools that this role will build in conjunction with other colleagues. These tools will enable the organization to make faster, smarter, and more informed decisions primarily supporting investment decisions but also operational workflows. The role will partner closely with Investments, Asset Management, Finance, Revenue Management, and Executive Leadership, in particular the CEO and CIO of Maymont.
The ideal candidate combines strong technical expertise in data science with financial and strategic thinking. This individual is equally comfortable building predictive models, analyzing investment opportunities, evaluating housing markets, and presenting analytical insights to executive leadership. Success in this role requires curiosity, business acumen, and the ability to transform complex data into actionable investment recommendations.
More specifically, the candidate has the intellectual range to receive a thesis-level research question, such as “where should we be investing given the silver tsunami demographic shift?”, and return within two weeks with a geospatial analysis, investment thesis, and platform-specific recommendations to deploy capital. The person possesses investment judgment, not just analytical skills, and is fluent in AI-assisted development tools that allow them to build and ship the tools that make research actionable.
Essential Job Functions
- Own a self-managed research roadmap driven by senior executive priorities, conducting independent deep-dive research sprints (typically 1–3 weeks) that deliver investment-grade analysis spanning full U.S. Housing platform: single-family rental, build-to-rent, senior housing, affordable housing, manufactured housing, and market-rate multifamily.
- Translate completed research into deployed, dynamic tools within our proprietary analytics application. For example, by converting a geospatial demographic analysis into an interactive heat map tool that enables platform-level investment decisions. This requires fluency in AI-assisted development workflows (e.g., Claude Code or similar agentic coding environments) to move from research output to working product without dependence on a separate engineering team.
- Analyze housing market trends, demographic shifts, competitive positioning, and macroeconomic factors impacting investment performance.
- Translate complex analytical findings into concise recommendations for executive leadership and investment teams.
- Collaborate with Data Engineering to ensure scalable, reliable, and trusted analytical datasets.
- Evaluate emerging technologies, modeling techniques, and external data sources to continuously improve model performance, scalability, and analytical capabilities.
- Perform other duties as assigned to support business objectives
Performance Expectations & Key Metrics:
Performance will be evaluated based on measurable outcomes aligned with company and departmental goals. Metrics may include:
- Decision Support: Develop analytical frameworks that improve market analysis, portfolio optimization, and overall investment performance.
- Strategic Analysis: Identify emerging opportunities and risks through advanced analytics, statistical modeling, and machine learning.
- Research Impact: Deliver platform-spanning investment research that directly informs capital deployment decisions measured by speed of thesis-to-recommendation cycle (target: 2 weeks for a defined research question), quality of cross-platform opportunity identification, and the degree to which research outputs result in deployed tools or funded investments.
- Analytical Innovation: Leverage AI, machine learning, automation, and emerging technologies to improve modeling capabilities and organizational efficiency.
- Data Quality & Analytical Standards: Ensure analytical rigor, statistical integrity, reproducibility, and documentation across all models and analyses.
Required Qualifications
Education
- Bachelor's or master's degree in Data Science, Statistics, Economics, Finance, Applied Mathematics, Computer Science, Engineering, or a related quantitative field.
Experience
- Minimum of 8-10 years of experience in quantitative research, data science, or applied analytics, with demonstrated investment-side experience (investment committee exposure, memo writing, or capital deployment decisions preferred).
Skills & Competencies
- Data Science & Machine Learning: Strong understanding of statistical modeling, predictive analytics, forecasting, optimization techniques, clustering, regression, machine learning methodologies, and the model development lifecycle (training, validation, deployment, and monitoring).
- Investment & Financial Analysis: Experience evaluating investment opportunities through quantitative analysis, financial modeling, forecasting, scenario analysis, and portfolio performance measurement.
- Real Estate Analytics: Experience analyzing housing markets, rental pricing, acquisition underwriting, portfolio optimization, demographic trends, geospatial data, competitive intelligence, and macroeconomic indicators affecting residential real estate investments.
- Programming & Engineering: Advanced proficiency in Python and SQL, with experience using common data science and machine learning libraries (e.g., pandas, scikit-learn, and modern ML frameworks).
- Artificial Intelligence: Experience leveraging Generative AI, Large Language Models (LLMs), and agentic workflows to automate research, generate market intelligence, and improve analytical efficiency.
- Strategic Thinking: Ability to frame ambiguous business problems, develop analytical approaches, and translate findings into strategic recommendations.
- Communication: Ability to clearly communicate complex analytical concepts to technical and non-technical audiences.
- Strong problem-solving skills and attention to detail.
- Demonstrated ability to influence strategic business decisions through analytical insights.
- Excellent communication, collaboration, and presentation skills with both technical and executive stakeholders.
Preferred Qualifications
- Master's degree or PhD in Data Science, Statistics, Economics, Finance, Operations Research, or MBA with a quantitative focus.
- Experience within real estate, private equity, investment management, asset management, or financial services.
- Experience building and deploying predictive pricing, forecasting, or optimization models in production.
- Experience utilizing geospatial analytics and external market data sources.
- Experience with AWS cloud services and modern AI platforms.
- Familiarity with Git, Agile development methodologies, and collaborative software development practices.
Why work for Maymont Homes?
Our Mission - " We Positively Impact the Lives in the Communities We Serve ." Every role contributes to this purpose, helping families find a place to call home while making a difference in the communities we support.
Certified Great Place to Work® - Our people make us who we are. This certification celebrates the values and culture that fuel collaboration, innovation, and care.
Outstanding Benefits - Backed by Brookfield, our benefits include a 5% 401(k) match, wellness credits that reduce healthcare costs, and up to 160 hours of PTO annually for full-time employees.
Career Growth - With continued expansion planned for Maymont, you'll find meaningful opportunities to grow your skills, advance your career, and make an impact.
Strong Foundation - As part of Brookfield Asset Management, one of the world's largest real estate asset managers, we have the stability, resources, and vision to keep growing.
Equal Opportunity Employer: Minorities/Religion/Sex/Protected Veterans/Disability/Sexual Orientation/Gender Identity/Marital Status/Pregnancy/Age/National Origin/Genetic Information. #MYMT
See All 9 Data Analytics Engineer Jobs in South Carolina
Find roles in South Carolina that match your experience and apply in just a few clicks.
Find Data Analytics Engineer JobsData Analytics Engineer Jobs by City in South Carolina
Where South Carolina roles are concentrated, by current openings.
Data Analytics Engineer Job Market in South Carolina
A snapshot from current South Carolina openings, updated as new roles post.
Who's Hiring
- Cognizant1

- Ryder System1

- Forward Edge AI1F
- Regional Finance1

- Furman University1

Top Industries Hiring
- Education1
- Construction & Real Estate1
What South Carolina Employers Look For
The qualifications that appear most often in data analytics engineer jobs across South Carolina.
- Bachelor's degree in computer science, data science, or a related quantitative field
- Proficiency in SQL and at least one scripting language such as Python or Scala
- Experience building and maintaining data pipelines using tools like dbt or Apache Airflow
- Hands-on work with cloud data platforms such as Snowflake, Databricks, or AWS Redshift
- Ability to translate business requirements into data models and analytical workflows
- Familiarity with version control practices and collaborative development using Git
Data Analytics Engineer Jobs in South Carolina: Frequently Asked Questions
How do you become a data analytics engineer in South Carolina?
Data analytics engineering carries no state-issued license in South Carolina, so the path runs through education and demonstrated technical skill. Most South Carolina employers expect a bachelor's degree in computer science, information systems, or a related field. Candidates who complete a degree at Clemson University, the University of South Carolina, or a comparable program and build a portfolio of pipeline and data modeling projects are well positioned for entry-level roles across the state's manufacturing, healthcare, and financial services sectors.
How much do data analytics engineers make in South Carolina?
Data analytics engineers in South Carolina earn a median of about $91,990 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $61,600 for the lowest 10% to over $156,000 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data analytics engineers in South Carolina?
Companies currently hiring data analytics engineers in South Carolina include Cognizant, Ryder System, and Forward Edge AI, per current listings on Migrate Mate as of July 2026. South Carolina's mix of large healthcare insurers, multinational manufacturers, and financial services firms creates steady, varied demand for analytics engineering talent across the state.
Which South Carolina cities have the most data analytics engineer jobs?
Columbia, Fort Mill, and Greenville lead South Carolina for data analytics engineer openings. Columbia anchors the market as the state capital and home to BlueCross BlueShield of South Carolina and a dense cluster of state government agencies, while Greenville reflects the Upstate's manufacturing-driven analytics demand from companies like Michelin and BMW, and Charleston draws openings from its growing technology and logistics sector.
Are there remote data analytics engineer jobs in South Carolina?
Yes, and more than most fields. About 60% of data analytics engineer openings tied to South Carolina are remote or hybrid as of July 2026, reflecting how naturally this work translates to distributed environments. Pipeline development, data modeling, and BI dashboard work in particular are frequently performed fully remote, making South Carolina-based candidates competitive for openings posted by employers anywhere in the country.
How can I get hired as a data analytics engineer in South Carolina with little or no experience?
The most realistic entry path is a junior data analyst or analytics associate role at a large South Carolina employer, then transitioning into engineering work once pipeline and modeling experience is established. BlueCross BlueShield of South Carolina and state government agencies in Columbia regularly bring on new-grad analysts. Building a portfolio with public datasets, earning a cloud certification such as AWS Certified Data Engineer, and contributing to open-source dbt projects strengthens applications considerably for candidates without professional experience.
Where can I find and apply to data analytics engineer jobs in South Carolina?
You can find and apply to data analytics engineer jobs in South Carolina on Migrate Mate, which lists current South Carolina openings updated regularly. Search the listings for roles that match your experience and specialization, then apply directly to the ones that fit.
See All 9 Data Analytics Engineer Jobs in South Carolina
Find roles in South Carolina that match your experience and apply in just a few clicks.
Find Data Analytics Engineer Jobs