1

Data Engineer Data Analyst Jobs in North Carolina

We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and ... Data Analyst Charlotte, NC Full-time Insurance Domain Analytics & Reporting * Turn business ...

Data Analyst

Charlotte, NC · On-site

$75 - $110/hr

We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and ... Data Analyst Charlotte, NC Full-time Insurance Domain Analytics & Reporting * Turn business ...

Data Scientist under general supervision will perform data engineering, data modeling and model deployment. Analyze large scale complex business data (time series data, structured/unstructured) from ...

Position Data Analyst - Manufacturing & Engineering Department Engineering Manager Engineering Manager Job Type Full-Time - Exempt Location On-Site - Burlington, NC Job Details Company Background ...

CapTech's Data Analysts work within a collaborative, team environment to help define and deliver ... Collaborate with other data workstreams (Data Engineers, Data Architects, Data Scientists, Product ...

CapTech's Data Analysts work within a collaborative, team environment to help define and deliver ... Collaborate with other data workstreams (Data Engineers, Data Architects, Data Scientists, Product ...

Data Analyst

Raleigh, NC · On-site

$27 - $28/hr

Data Analytics / Data Engineer Contractor This role supports two major system overhaul projects and is expected to last at least 6 months, likely closer to 12 months. The manager is seeking someone ...

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

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

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

Data Engineer

Charlotte, NC · On-site

$53K - $88K/yr

Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public Trust What You Will Do: Guidehouse seeks a Data Engineer I to support the development, maintenance, and ...

ClifyX is focused on data engineering and science, and they are seeking a Data Engineer/ Scientist to create and maintain engineering systems for data analytics. The role involves compiling data from ...

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

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

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

Data Architect

Charlotte, NC · On-site

$62.25 - $80/hr

Senior Data Engineer / Data Architecture Charlotte, NC We re looking for a hands-on Senior Data Engineer who s ready to take the next step into data architecture. This role is approximately 70% hands ...

Data Engineer

Charlotte, NC · On-site

$111K - $134K/yr

Charlotte, NC Duration: Long term Skills - Python, Pyspark, GCP, ETL-Big Data/Data Warehouse, Data Analytics, SQL, Git * BS or MS degree in computer science, computer engineering, or other technical ...

next page

Showing results 1-20

Data Engineer Data Analyst information

How do data engineer data analysts typically collaborate with data scientists and business stakeholders?

Data Engineer Data Analysts play a crucial role in bridging the technical and analytical needs of an organization. They work closely with data scientists by preparing, cleaning, and structuring large datasets to enable advanced analytics and modeling. Additionally, they collaborate with business stakeholders to understand data requirements, translate business questions into technical solutions, and deliver actionable insights. Effective communication and teamwork are essential, as the role often involves facilitating data access, ensuring data quality, and aligning data projects with business objectives.

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

To thrive as a Data Engineer/Data Analyst, you need strong analytical and statistical skills, proficiency in programming languages like Python or SQL, and typically a degree in computer science, statistics, or a related field. Familiarity with data warehousing tools, ETL processes, and experience with platforms like Hadoop, Spark, or Tableau is often required. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for interpreting data and sharing insights with stakeholders. These competencies ensure accurate data management, insightful analysis, and support data-driven decision-making within organizations.

What is the difference between Data Engineer Data Analyst vs Data Scientist?

AspectData EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; often certifications in cloud or data toolsBachelor's or higher in CS, Statistics, or related; often advanced degrees
Work EnvironmentBuilds data pipelines, manages databases, ensures data flowAnalyzes data, creates models, interprets insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceResearch firms, tech, finance, marketing

Data Engineers focus on developing and maintaining data infrastructure, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but Data Engineers are more involved in data architecture, whereas Data Scientists focus on modeling and analysis.

Can a data analyst work as a data engineer?

A data analyst can transition to a data engineer role by developing skills in data pipeline development, database management, and programming languages like Python or SQL. While data analysts focus on data interpretation and reporting, data engineers build and maintain data infrastructure, often requiring knowledge of tools such as Apache Spark, Hadoop, or cloud platforms. Gaining experience with these technologies and earning relevant certifications can facilitate the switch between roles.

What job categories do people searching Data Engineer Data Analyst jobs in North Carolina look for?

The top searched job categories for Data Engineer Data Analyst jobs in North Carolina are:

What cities in North Carolina are hiring for Data Engineer Data Analyst jobs?

Cities in North Carolina with the most Data Engineer Data Analyst job openings:

Infographic showing various Data Engineer Data Analyst job openings in North Carolina as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Data Analyst

DATAECONOMY

Charlotte, NC • On-site

Full-time

Posted 19 days ago


Job description

DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.

 

We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.


Data Analyst
Charlotte, NC
Full-time
Insurance Domain
Analytics & Reporting

  • Turn business questions from underwriting, claims, actuarial, and finance teams into well-structured analyses and repeatable reports.
  • Build and maintain dashboards and scorecards for KPIs such as loss ratio, combined ratio, premium growth, retention/lapse, and claims cycle time.
  • Perform exploratory analysis to surface trends, anomalies, and opportunities (e.g., emerging loss patterns, fraud indicators, leakage).
  • Document assumptions, definitions, and methodology so results are transparent and auditable.

Insurance Domain Analytics

  • Analyze policy, premium, claims, and billing data to support pricing, reserving, and portfolio management discussions.
  • Support loss-ratio, frequency/severity, and retention/churn analyses for P&C and/or L&A lines of business.
  • Partner with actuarial and underwriting teams to validate data and interpret results in business context.

Data Preparation & SQL

  • Write and optimize SQL to extract, join, and aggregate data from the lakehouse / data warehouse.
  • Profile, clean, and validate datasets; flag and help resolve data quality issues with engineering.
  • Build reusable, well-documented queries, views, and semantic-layer definitions.

Visualization & Stakeholder Enablement

  • Design clear, decision-oriented visualizations in Power BI / Tableau (or equivalent).
  • Translate analysis into concise narratives and recommendations for non-technical business stakeholders.
  • Enable self-service by documenting metrics and curating trusted data sources.

Technology Stack

  • Strong SQL across cloud data warehouse / lakehouse environments (Databricks SQL, Snowflake, BigQuery, or similar).
  • BI/visualization tools  Power BI and/or Tableau.
  • Spreadsheet modeling (Excel) for ad-hoc analysis.
  • Working knowledge of Python (pandas) for data wrangling is a plus.

Required Qualifications

  • 4–7+ years of experience in data analysis, business intelligence, or reporting.
  • Strong, demonstrable SQL skills (complex joins, window functions, aggregations, query tuning).
  • Proven experience building dashboards and reports in Power BI and/or Tableau.
  • Solid understanding of data modeling concepts (dimensional / star schema) from a consumer's perspective.
  • Ability to translate ambiguous business questions into structured analysis and clear deliverables.
  • Strong written and verbal communication with business stakeholders.

Preferred Skills

  • Insurance domain knowledge P&C and/or Life & Annuities; familiarity with premium, claims, and loss-ratio concepts.
  • Experience with cloud data platforms (Databricks, Snowflake, Azure/AWS/GCP).
  • Python (pandas) or R for analysis and automation.
  • Statistical analysis fundamentals and A/B or cohort analysis experience.
  • Exposure to data governance, metadata, and trusted-source / semantic-layer practices.
  • Awareness of PII/PHI handling and regulated-data sensitivity.

Requirements
  • Strong SQL complex joins, window functions, aggregation, query tuning
  • Power BI and/or Tableau dashboard and report development
  • Data modeling literacy dimensional / star schema (consumer perspective)
  • Ability to translate business questions into structured analysis
  • Strong stakeholder communication and storytelling
  • 4–7+ years in data analysis / BI / reporting

BenefitsStandard full-time benefits.