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Data Engineer Project Jobs in Missouri (NOW HIRING)

Senior AWS Software Data Engineer

Hazelwood, MO · On-site

$115K - $152K/yr

Senior AWS Software Data Engineer Company: The Boeing Company The Boeing Company is looking for a ... Leads execution and documentation of software data research and development projects * Consults on ...

Senior AWS Software Data Engineer

Hazelwood, MO · On-site

$115K - $152K/yr

Senior AWS Software Data Engineer Company: The Boeing Company The Boeing Company is looking for a ... Leads execution and documentation of software data research and development projects * Consults on ...

Senior AWS Software Data Engineer

Hazelwood, MO · On-site

$115K - $152K/yr

Senior AWS Software Data Engineer Company: The Boeing Company The Boeing Company is looking for a ... Leads execution and documentation of software data research and development projects * Consults on ...

Azure Databricks Data Engineer Fractal is a strategic AI partner to Fortune 500 companies with a ... The may be subject to modification based on business requirements and evolving project needs. Pay:

New

Principal Engineer

Creve Coeur, MO · On-site

$157.25 - $185/hr

Reporting to the Global Head of Data Architecture & Engineering, the Principal Data Engineer is expected to move fluidly across Data Engineering teams - embedding in projects for days or months at a ...

Talend Data Engineer Location: St. Louis, MO Duration: 12 Months Plus Possible Extension Job ... Must have worked on projects that have resulted in code being deployed to production â Experience ...

Data Strategy-Manager

Kansas City, MO · On-site

$99K - $232K/yr

Take ownership of projects, ensuring their successful planning, budgeting, execution, and ... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP ...

Showing results 41-60

Data Engineer Project information

What is a data engineer project?

A Data Engineer Project refers to a specific initiative or assignment undertaken by data engineers to design, build, and maintain systems that gather, process, and store large volumes of data. These projects often involve creating data pipelines, integrating multiple data sources, ensuring data quality, and optimizing storage solutions for analytics or business intelligence. Such projects are critical for organizations to manage their data efficiently and enable data-driven decision-making. Data Engineer Projects can range from building a data warehouse to implementing real-time data streaming solutions.

What are some common challenges faced by data engineers working on project-based teams?

Data Engineers on project-based teams often encounter challenges such as integrating data from disparate sources, ensuring data quality and consistency, and meeting tight project deadlines. Collaboration with data scientists, analysts, and software engineers is crucial, requiring clear communication to translate business needs into robust data pipelines. Additionally, adapting to evolving technologies and toolsets is essential for the successful delivery of scalable and maintainable solutions.

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

To thrive as a Data Engineer, you need strong proficiency in programming (Python, Java, or Scala), data modeling, and database management, often supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), ETL systems, cloud platforms (AWS, Azure, GCP), and relevant certifications is highly beneficial. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with data teams and stakeholders. These competencies are essential for building reliable data pipelines and ensuring data availability and quality to drive business insights.

What is the difference between Data Engineer Project vs Data Engineer?

AspectData Engineer ProjectData Engineer
CredentialsTypically requires a degree in Computer Science, Data Science, or related fields; certifications like AWS, Google Cloud, or Azure are commonSimilar credentials; often holds certifications in cloud platforms and data tools
Work EnvironmentProject-based, often temporary teams working on specific data solutionsFull-time role within organizations, maintaining ongoing data pipelines and infrastructure
Industry UsageUsed across industries for specific data initiativesCore role in data-driven companies and departments
Search & Comparison IntentOften searched for project-based roles or freelance opportunitiesMore common in job searches for permanent positions

In summary, Data Engineer Projects focus on temporary, goal-specific data tasks, while Data Engineers hold ongoing roles responsible for maintaining data infrastructure. Both roles require similar skills and certifications but differ mainly in scope and employment type.

Are data engineers still in high demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. Skills in cloud platforms, data pipeline development, and tools like SQL, Python, and Apache Spark enhance job prospects in this field.

Is a data engineer paid well?

Data engineers are generally well-compensated due to their specialized skills in managing large datasets, working with tools like SQL, Python, and cloud platforms. Salaries vary by experience, location, and industry, but they tend to be higher than average for tech roles, reflecting the demand for data infrastructure expertise.

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

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

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

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

Senior Geospatial Data Engineer

Object Computing, Inc.

Saint Louis, MO • On-site

$103K - $140K/yr

Full-time

Re-posted 6 days ago


Job description

Object Computing, Inc. is seeking a Senior Geospatial Data Engineer to join our Xtrack Product Team. In this role, you will lead the design and implementation of scalable, cloud-based geospatial data infrastructures, and play a key part in shaping our data architecture and product engineering strategy with a focus on improving safety and operational efficiencies for organizations in the rail industry. You will work with cutting-edge technologies in image processing, artificial intelligence, cloud computing, and geospatial database management. Your work will optimize complex business processes and unlock new value from large-scale geospatial datasets.
What you will do:
  • Architect, design, and maintain robust, scalable data pipelines and infrastructures for geospatial and big data applications maintaining a focus on performance and the ultimate end-user product experience.
  • Lead the development and optimization of ETL processes for ingesting, cleaning, transforming, and storing large volumes of geospatial and tabular data.
  • Design, build, and interact with API-driven, service-to-service web services (using FastAPI, Litestar, Flask, etc.) to enable integration across a suite of products.
  • Collaborate with backend and platform engineers to ensure secure, reliable, and scalable service-to-service communication.
  • Translate complex analytics and business questions into actionable, production-grade data solutions.
  • Collaborate closely with data scientists, analysts, and business stakeholders to deliver high-impact data products.
  • Drive the adoption and optimization of cloud-based data solutions (e.g., GCP, AWS, Azure).
  • Ensure data quality, integrity, and security across all stages of the data lifecycle.
  • Mentor and provide technical guidance to junior data engineers and team members.
  • Communicate technical details and insights clearly to both technical and non-technical audiences, including leadership.
  • Proactively recommend and implement improvements to existing data infrastructure and software programs.
  • Stay current with industry trends and emerging technologies in geospatial data engineering.
What you will bring:
  • An excitement and dedication towards manifesting real and measurable impact for customers and clients and a dedication to being a team player towards achievement of those outcomes.
  • Experience in software development, data engineering, or big data roles, preferably with a focus on geospatial data.
  • Experience building solutions with Python.
  • Experience with relational databases (e.g., SQL), including advanced query building, data extraction, and manipulation.
  • Experience architecting and optimizing cloud-based data solutions (preferably GCP, AWS, or Azure).
  • Deep experience with big data technologies such as Hadoop, Spark, MapReduce, or Kafka.
  • Experience integrating with API-driven, service-to-service web services.
  • Demonstrated ability to lead projects, mentor team members, and drive technical decisions.
  • Strong problem-solving skills, resourcefulness, and ability to work independently or collaboratively.
  • Excellent organizational, interpersonal, and communication skills.
What will make you stand out:
  • Expertise with geospatial libraries and tools (e.g., GDAL, PDAL, PostGIS, GeoPandas, Shapely).
  • Experience deploying and scaling machine learning (ML) models/algorithms in production.
  • Strong experience with geospatial analytics and working with geospatial data formats (e.g., LAS, LAZ, COPC, GeoTIFF, Shapefiles).
  • Experience leading teams in integrating and scaling complex ML/Deep Learning (DL) algorithms.
  • Experience working with LiDAR data and deriving real-world insights from point clouds.
  • Experience with ESRI products (ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise) or other GIS platforms.
  • Experience with data streaming, real-time data processing, or cloud-native geospatial solutions.
  • Cloud certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Data Analytics).
  • Experience with OAuth, authentication, and API key management for secure service-to-service communication.
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.
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