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Data Infrastructure Analyst Jobs in Missouri (NOW HIRING)

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · On-site

$113K - $136K/yr

... and analysis. You will play a pivotal role in managing data infrastructure, optimizing data workflows, and guiding data-driven strategies while working closely with data scientists and other ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113K - $136K/yr

... and analysis. You will play a pivotal role in managing data infrastructure, optimizing data workflows, and guiding data-driven strategies while working closely with data scientists and other ...

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

Partner with analytics, marketing, commercial operations, and core technology/cybersecurity teams to deliver fit-for-purpose commercial data products * Monitor and optimize data infrastructure costs ...

Shelter Insurance

Senior Data Architect

Columbia, MO · On-site

$127K - $157K/yr

Play a critical role in defining and implementing a scalable and robust data infrastructure that supports the company's analytical and operational needs. * This position requires expertise in data ...

Washington University of St. Louis

... Infrastructure, Capital Programs & Real Estate (EPO) department at WashU provides integrated ... Data Analytics & Performance Reporting * Develops, maintains, and enhances dashboards, reporting ...

MFour Mobile Research, Inc.

Data Engineer

Kansas City, MO · On-site

$111K - $134K/yr

Our Story: Founded in 2011, MFour is a fast-growing data and analytics technology company ... Your Mission: * Data Infrastructure Development: * Design, build, and maintain scalable data ...

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Data Infrastructure Analyst information

What is a data infrastructure analyst?

Data Infrastructure Analysts are professionals who design, maintain, and optimize the systems and architecture that store, process, and manage an organization's data. They work with databases, data warehouses, and cloud storage solutions to ensure data is accessible, reliable, and secure. Their role often involves collaborating with data engineers, IT teams, and business analysts to support data-driven decision-making. Data Infrastructure Analysts also monitor system performance, troubleshoot issues, and recommend improvements to enhance data management processes.

What are the key skills and qualifications needed to thrive as a data infrastructure analyst?

To thrive as a Data Infrastructure Analyst, you need a solid background in database management, data modeling, and systems analysis, often supported by a degree in computer science or a related field. Familiarity with SQL, ETL tools, cloud platforms (such as AWS or Azure), and certifications like AWS Certified Data Analytics or Google Cloud Data Engineer are commonly required. Strong problem-solving abilities, attention to detail, and effective communication help analysts collaborate across technical and business teams. These skills are crucial for ensuring robust, scalable data systems that support organizational decision-making and operational efficiency.

What are some common challenges data infrastructure analysts face when managing large-scale data systems?

Data Infrastructure Analysts frequently encounter challenges such as ensuring data integrity across distributed systems, optimizing data pipelines for performance, and maintaining system scalability as data volumes grow. Balancing security requirements with accessibility, especially in environments with sensitive information, is also a key concern. Additionally, collaborating with data engineers, database administrators, and business teams to align infrastructure with organizational goals requires strong communication and adaptability.

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

AspectData Infrastructure AnalystData Engineer
Required CredentialsBachelor's in IT, Computer Science, or related field; certifications like Microsoft Certified Data AnalystBachelor's or higher in Computer Science, Software Engineering; certifications like AWS Certified Data Analytics
Work EnvironmentCorporate offices, data centers, cloud platformsDevelopment environments, cloud platforms, data pipelines
Employer & Industry UsageFinance, healthcare, retail, tech companiesTech firms, finance, e-commerce, large enterprises
Common Search & ComparisonYesYes

The Data Infrastructure Analyst focuses on maintaining and optimizing existing data systems, ensuring data accessibility and quality. In contrast, Data Engineers design, build, and implement data pipelines and infrastructure from scratch. Both roles require similar credentials and often work in overlapping environments, but their core responsibilities differ in scope and focus.

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

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

Data Infrastructure Analyst jobs near you

Data Engineer - Multiple Positions

Chesterfield, MO • On-site

Koantek
IT Services • 11 - 50 employees
Learn more about Koantekexternal

$113K - $136K/yr

Contractor

Re-posted 17 days ago

Job description


Location: United States - Remote
Employment Type: Full-Time and Contract
Data Engineer
Description:
As a Data Engineer at Koantek, you will leverage advanced data engineering techniques and analytics to support business decisions for our clients. Your role will involve designing and building robust data pipelines, integrating structured and unstructured data from various sources, and developing tools for data processing and analysis. You will play a pivotal role in managing data infrastructure, optimizing data workflows, and guiding data-driven strategies while working closely with data scientists and other stakeholders.
The impact you will have:
  • Guide Big Data Transformations: Implementation of comprehensive big data projects, including the development and deployment of innovative big data and AI applications.
  • Ensure Best Practices: Guarantee that Databricks best practices are applied throughout all projects to maintain high-quality service and successful implementation.
  • Support Project Management: Assist the Professional Services leader and project managers with estimating efforts and managing risks within customer proposals and statements of work.
  • Architect Complex Solutions: Design, develop, deploy, and document complex customer engagements, either independently or as part of a technical team, serving as the technical lead and authority.
  • Enable Knowledge Transfer: Facilitate the transfer of knowledge and provide training to team members, customers, and partners, including the creation of reusable project documentation.
  • Contribute to Consulting Excellence: Share expertise with the consulting team and offer best practices for client engagement, enhancing the effectiveness and efficiency of other teams.

Requirements
Minimum qualifications:
  • Educational Background: Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).
  • Experience:
    • 3+ years of experience as a Data Engineer, with proficiency in at least two major cloud platforms (AWS, Azure, GCP).
    • Proven experience in designing, developing, and implementing comprehensive data engineering solutions using Databricks, specifically for large-scale data processing and integration projects
    • Develop scalable streaming and batch solutions using cloud-native components.
    • Perform data transformation tasks, including cleansing, aggregation, enrichment, and normalisation, utilising Databricks and related technologies.
    • Experience in applying DataOps principles and implementing CI/CD and DevOps practices within data environments to optimize development and deployment workflows.
  • Technical Skills:
    • Expert-level proficiency in Spark Scala, Python, and PySpark.
    • In-depth knowledge of data architecture, including Spark Streaming, Spark Core, Spark SQL, and data modeling.
    • Hands-on experience with various data management technologies and tools, such as Kafka, StreamSets, and MapReduce.
    • Proficient in using advanced analytics and machine learning frameworks, including Apache Spark MLlib, TensorFlow, and PyTorch, to drive data insights and solutions.
  • Databricks Specific Skills:
    • Extensive experience in data migration from on-premises to cloud environments and in implementing data solutions on Databricks across cloud platforms (AWS, Azure, GCP).
    • Skilled in designing and executing end-to-end data engineering solutions using Databricks, focusing on large-scale data processing and integration.
    • Proven hands-on experience with Databricks administration and operations, including notebooks, clusters, jobs, and data pipelines.
    • Experience integrating Databricks with other data tools and platforms to enhance overall data management and analytics capabilities.
  • Good to have Certifications:
    • Certification in Databricks Engineering (Professional)
    • Microsoft Certified: Azure Data Engineer Associate
    • GCP Certified: Professional Google Cloud Certified.
    • AWS Certified Solutions Architect Professional

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