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Data Engineer Data Analyst Jobs in Missouri (NOW HIRING)

Data Analyst

Kansas City, MO · On-site

$65K - $85K/yr

The Data Analyst works closely with the Data Engineer/Data Project Lead, Data Visualization Specialist, and program staff to ensure analyses are methodologically sound, aligned with user needs, and ...

This is not a Data Engineer role . Candidates must have a strong analytics and data validation background. Key Responsibilities * Perform data validation and quality checks using SQL and Python

... 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 Analyst As Bayer Crop Science's Digital Farming arm, we deliver sustainable digital solutions ... Partner with Commercial, Data Engineering and Science teams to provide better insights into product ...

Data Analyst

Creve Coeur, MO · On-site

$71K - $135K/yr

Data Analyst As Bayer Crop Science's Digital Farming arm, we deliver sustainable digital solutions ... Partner with Commercial, Data Engineering and Science teams to provide better insights into product ...

... 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

Saint Louis, MO · On-site

$110K - $133K/yr

This role will work across cloud platforms, digital systems, and analytics tools to ensure our data ... The Data Engineer will help build the foundation that powers these experiences. Responsibilities:

Data Engineer

Kansas City, MO

$111K - $134K/yr

Implement medallion/lakehouse architectures, dimensional models, and data transformation workflows to support analytics and reporting use cases Engineer solutions using technologies such as PySpark ...

Data Engineer

Kansas City, MO · On-site

$111K - $134K/yr

Implement medallion/lakehouse architectures, dimensional models, and data transformation workflows to support analytics and reporting use cases * Engineer solutions using technologies such as PySpark ...

Senior Data Analyst

Saint Louis, MO · On-site

$83K - $105K/yr

Developer Collaboration & Bridge: Conduct detailed walkthroughs of mapping documents with ... Analyze domain-specific data entities, including household relationships, investment portfolios ...

New

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

Remote The Biotech Data Engineer focuses on designing, building, and maintaining scalable Azure Databricks-based data pipelines and architectures that enable analytics, AI/ML, and reporting across ...

Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

Work closely with data analysts, cloud engineers, and application developers * Integrate data solutions with other components of the migrated applications * Participate in Agile ceremonies (Sprint ...

Position Summary The Data Analyst collaborates with business users to create report specifications ... Curiosity to learn and explore new technologies or programming languages to enhance skills and ...

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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 are popular job titles related to Data Engineer Data Analyst jobs in Missouri?

For Data Engineer Data Analyst jobs in Missouri, the most frequently searched job titles are:

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

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

What cities in Missouri are hiring for Data Engineer Data Analyst jobs?

Cities in Missouri with the most Data Engineer Data Analyst job openings:

Infographic showing various Data Engineer Data Analyst job openings in Missouri as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 82% In-person, 7% Hybrid, and 11% Remote job distribution.

Data Engineer/Data Analyst

Advantage Tech

Kansas City, MO • On-site

Full-time

Posted 29 days ago


Job description

Data Engineer/Analyst
Position Summary
The Data Engineer/Data Analyst is responsible for designing, building and maintaining our cloud-based data ecosystem while also delivering high-value analytics, reporting, and business insights. You'll work across the full data lifecycle - from engineering and modeling to visualization and strategic analysis - ensuring the organization has reliable, scalable, and actionable data.
KEY RESPONSIBILITIES
Data Engineering & Architecture (Primary Responsibility)
  • Design, provision, and configure cloud data warehouse and storage environments (e.g., Azure Synapse, Data Lake, Fabric).
  • Develop, test, and maintain scalable ETL/ELT pipelines using SQL, Azure Data Factory, Python, or similar tools.
  • Architect and implement dimensional models, data marts, and data cubes to support analytics and reporting needs.
  • Ensure data quality, reliability, and performance across all pipelines and data structures.
  • Create clear, comprehensive documentation for data systems, pipelines, and processes.

Analytics, Reporting & Business Insights (Secondary Focus)
  • Build and maintain impactful dashboards, reports, and visualizations using tools such as Power BI, Tableau, or Looker.
  • Partner with business stakeholders to understand analytical needs and translate them into technical solutions.

Cross-Functional Collaboration & Strategy
  • Work closely with the team to ensure alignment on architecture, governance, and best practices.
  • Support the evolution of the organization's data strategy by identifying opportunities for automation, optimization, and improved insight delivery.
  • Contribute to the long-term vision of a scalable, modern data ecosystem that empowers business users.

QUALIFICATIONS
Knowledge, Skills and Abilities
Required:
  • Expert SQL Skills: Mastery of SQL for complex querying, performance tuning, and data manipulation.
  • Cloud Experience: Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP) in relation to data services.
  • Programming: Strong proficiency in Python for data manipulation and pipeline development.
  • Data Visualization: Experience building reports and dashboards with a major BI tool (e.g., Tableau, Looker, Power BI).
  • Strong organizational, planning, and problem-solving skills
  • Proven ability to manage deadlines and priorities in a fast-paced environment
  • Excellent written and verbal communication skills
  • Familiarity with ERP systems (Epicor P21 preferred), WMS, or operational reporting tools
  • Execution-focused with strong follow-through
  • Detail-oriented while able to see the bigger picture
  • Results-driven mindset aligned with business outcomes

Nice-to-Have Skill:
  • AI/ML Familiarity: Understanding of data preparation for Artificial Intelligence (AI) and Machine Learning (ML) models and experience with related data tools.

Education and Experience
  • Technical Proficiency: 3+ years of professional experience in data engineering, ETL development, and data modeling.
  • Experience with specific tools mentioned (Azure Data Factory, Power BI, etc.).
  • Experience in Business Analysis or formal requirements gathering.
  • Bachelor's degree in business, Information Systems, Computer Science or related field preferred
  • Experience managing cross-functional initiatives with multiple stakeholders a plus
  • Experience in industrial distribution, manufacturing, or supply chain environments preferred
  • Experience supporting process improvement or operational transformation initiatives

Physical Requirements
  • Prolonged periods of sitting at a desk and working on a computer.