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Software Engineer Data Analyst Jobs in Newfoundland and Labrador

Wood Plc

Asset Integrity Engineer

Saint John's, NL · On-site

Travel when required to client location to coordinate data collection and data QA / QC, perform ... Have experience in corrosion analysis, material specifications and selection, testing, manufacture ...

Micro1

Remote Aerodynamics Expert

Corner Brook, NL · Remote

... aerospace engineering mechanical engineering thermofluids experimental methods technical ... analysis About micro1 micro1 is the leading AI data lab for training frontier models and evaluating ...

Micro1

Remote Aerodynamics Expert

Saint John's, NL · Remote

... aerospace engineering mechanical engineering thermofluids experimental methods technical ... analysis About micro1 micro1 is the leading AI data lab for training frontier models and evaluating ...

Micro1

Remote Aerodynamics Expert

Labrador City, NL · Remote

... aerospace engineering mechanical engineering thermofluids experimental methods technical ... analysis About micro1 micro1 is the leading AI data lab for training frontier models and evaluating ...

Micro1

Remote Aerodynamics Expert

Mount Pearl, NL · Remote

... aerospace engineering mechanical engineering thermofluids experimental methods technical ... analysis About micro1 micro1 is the leading AI data lab for training frontier models and evaluating ...

Dyno Nobel

Field Consultant

Labrador City, NL · On-site

Ability to communicate clearly and confidently with blasters, supervisors, engineers, and clients - even when things aren't going well. * Working knowledge of blasting software, data analysis tools ...

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All JobsSoftware Engineer Data Analyst JobsSoftware Engineer Data Analyst Jobs in Newfoundland and Labrador

Software Engineer Data Analyst information

See Newfoundland and Labrador salary details

$30K

$114.6K

$189.5K

How much do software engineer data analyst jobs pay per year?

As of Aug 11, 2026, the average yearly pay for software engineer data analyst in Newfoundland and Labrador is $114,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,000.00 and $145,500.00 per year, depending on experience, location, and employer.

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

AspectSoftware Engineer Data AnalystData Scientist
Required CredentialsBachelor's in CS, Data Analysis, or related; programming skillsBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentSoftware development teams, data analysis projectsResearch, modeling, predictive analytics teams
Employer & Industry UsageTech companies, finance, healthcareTech firms, research institutions, finance
Common Search & ComparisonOften compared for data roles involving coding and analysisMore focused on predictive modeling and research

The main difference between a Software Engineer Data Analyst and a Data Scientist lies in their focus and skill set. Software Engineers Data Analysts primarily develop data tools and analyze data using programming, while Data Scientists focus on building predictive models and advanced analytics. Both roles require strong technical skills, but Data Scientists typically have more expertise in statistics and machine learning.

How do software engineer data analysts typically collaborate with other teams to deliver data-driven solutions?

Software Engineer Data Analysts work closely with cross-functional teams, including data scientists, product managers, and software developers, to collect requirements and translate business needs into actionable analytics solutions. They often participate in regular meetings to align on project goals, share progress, and troubleshoot data integration challenges. Effective communication is key, as they must explain technical findings to non-technical stakeholders and ensure that the data pipelines and dashboards they develop meet end-user needs. This collaborative environment provides opportunities to broaden technical skills and gain insights into various business functions.

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

To thrive as a Software Engineer Data Analyst, you need strong programming skills (such as Python or Java), a solid understanding of data structures and algorithms, and a background in statistics or computer science. Proficiency in SQL, data visualization tools (like Tableau or Power BI), and experience with big data platforms (such as Hadoop or Spark) are typically required, along with relevant certifications. Analytical thinking, problem-solving ability, and effective communication help you translate complex data into actionable insights. These skills ensure you can extract, analyze, and communicate data-driven solutions that support business objectives.

What is a software engineer data analyst?

A Software Engineer Data Analyst is a professional who combines software engineering skills with data analysis expertise to extract insights from data and build applications or tools for data processing. They typically design, develop, and maintain software systems that collect, store, and analyze large datasets. Their role often involves writing code to automate data workflows, create dashboards, and perform statistical analyses. These professionals work closely with other engineers, data scientists, and business stakeholders to support data-driven decision making.
Software Engineer Data Analyst jobs near you

Remote Materials Scientist / Engineer

Micro1

Bay Roberts, NL • Remote

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Materials Scientist / Engineer
$80 - $130/hourpay
Required Skills
materials science expertise
materials characterization
technical literature review
scientific data interpretation
clear written and verbal communication
remote collaboration
annotating technical datasets
scenario and case study development
quality assurance in scientific deliverables
analytical skills
About micro1
micro1 is the leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms that real-world expertise into high-quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.

Our platform identifies and vets top talent through an AI recruiter, enabling high-quality expert contributions at scale. We aim to enable 1 billion people to do meaningful work by applying their expertise to AI. As our global expert network grows, micro1 is building the human intelligence layer for frontier AI.

Role Title: Materials Scientist / Engineer


Role Type: Contractor


Location: Remote


micro1 is engaging Materials Scientists / Engineers to contribute their technical expertise to a customer’s advanced materials project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret scientific data from experimental results, technical datasets, and research publications in materials science and engineering.
  2. Conduct comprehensive technical literature reviews to identify key advances, methodologies, and challenges in materials characterization and related fields.
  3. Annotate and structure technical datasets with precise, detailed commentary and context to support AI model training.
  4. Develop realistic scenarios and case studies that represent practical applications and challenges within materials engineering, metallurgy, or related sectors.
  5. Provide clear, well-organized written and verbal explanations of materials phenomena, properties, and scientific reasoning.
  6. Review and assure the quality, consistency, and accuracy of scientific deliverables submitted for project milestones.
  7. Collaborate remotely with other scientific contributors, leveraging digital tools and documentation practices.


Preferred Qualifications

  1. MS or PhD in Materials Science & Engineering, Metallurgy, Mechanical Engineering, Chemical Engineering, or a related discipline with a materials specialization.
  2. Demonstrated expertise in materials characterization techniques (e.g., microscopy, spectroscopy, mechanical testing).
  3. Strong analytical skills and experience interpreting complex scientific data.
  4. Substantial experience conducting technical literature reviews and summarizing key findings.
  5. Proven ability to communicate complex technical concepts clearly, both in writing and verbally, to diverse audiences.
  6. Experience with quality assurance and review of scientific documents or datasets.
  7. Familiarity with remote collaboration tools and digital knowledge-sharing environments.


Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.


Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.


Apply