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Data Analyst
Morgan Stanley
About the role
We are looking for a Data Analyst to analyze and visualize large-scale IT infrastructure and asset data, building pipelines and dashboards for internal stakeholders.
The mandatory requirements are advanced SQL, experience building ETL/ELT pipelines with PySpark, Databricks, or Snowflake, 4+ years in data analytics, experience with large-scale IT infrastructure or asset datasets, Power BI, Tableau, or Qlik, hands-on use of GenAI tools, and strong English communication skills.
Must haves
- At least 4 years in Data Analytics, with strong quantitative and qualitative analytical skills and a proven track record of solving complex data problems.
- ETL/ELT Processing: Robust experience building ETL/ELT pipelines, ideally utilizing a PySpark / Databricks / Snowflake stack (or equivalent modern cloud technologies).
- Advanced SQL: Strong, production-grade SQL skills for complex querying, data joining, and analytical operations across large-scale systems.
- Large-Scale Asset & Infrastructure Datasets: Hands-on experience working with massive, enterprise-grade datasets related to IT infrastructure, hardware/software assets, network configurations, or cloud resources.
- Dashboarding & Business Intelligence: Proficient in creating interactive dashboards using Power BI (or similar tools such as Tableau/Qlik) to translate data into business narratives.
- Communication: Excellent oral and written communication skills, with the ability to lead data-focused discussions and customer-facing interactions independently.
- Frontier AI Technologies: Practical knowledge of and experience using cutting-edge AI technologies, Generative AI tools, and LLM framework integrations.
- Upper-intermediate English level.
Nice to haves
- ServiceNow & CMDB: Hands-on experience with ServiceNow data models, Configuration Management Databases (CMDB), or ServiceNow development experience is a huge plus.
- Authoritative Data Source (ADS) Strategy: Experience designing or maintaining strategies for enterprise authoritative data sources.
- Data Governance & Risk Management: Knowledge of enterprise data governance frameworks, compliance standards, internal audit protocols, and risk management processes.
- Data Transformation Expertise: Demonstrated expertise in end-to-end data mapping, complex transformations, and normalization across disparate datasets.
What you will do
- Data Analysis & Visualization: Design, build, and maintain interactive Power BI (or equivalent) dashboards to deliver clear metrics on enterprise infrastructure, assets, and operational risks.
- ETL/ELT Data Engineering: Develop, optimize, and maintain robust data transformation pipelines processing massive volumes of asset and infrastructure data.
- Stakeholder & Client Leadership: Directly engage with customers, business partners, and engineering teams to identify requirements, translate business needs into data solutions, and independently resolve complex data challenges.
- Data Querying & Modeling: Write complex, optimized SQL queries to manipulate, validate, and extract key insights from multi-source large-scale databases.
- AI & Automation Integration: Evaluate and leverage frontier AI tools and technologies to improve data processing workflows, analytical modeling, and operational efficiency.
- Data Quality & Governance: Assist in defining data mappings, transformations, and schema normalizations to maintain high standards of data integrity.
Perks
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
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Hiring process timeline
We designed our hiring process to be fast, transparent, and convenient — so you always know what to expect and can move through the steps without unnecessary delays.
A quick note
After applying, keep an eye on your inbox — including your spam folder. Occasionally, emails from our hiring platform, LaunchPod, may land there.
1
Tell us about yourself
Submit a short application form.
2
Pass a quick test
Pass a 30’- 60’ test.
3
Record a short video
Introduce yourself on video to fast-track your application process.
4
Meet our team
Once you pass the video review, grab a spot on our calendar for a technical interview.
5
Get an offer
Welcome to AgileEngine!
FAQ
Have any questions?
We are a remote-first company, so all our positions are remote. Schedules are flexible, but the main requirement is to have an overlap with your client’s schedule to ensure smooth collaboration. Specific details depend on the project and are discussed during the interview process.
We look for Upper-Intermediate (B2) proficiency or higher. Since you will be collaborating with international teams and global clients (including Fortune 500 companies), English is a part of your daily work.
It depends on your location. We provide equipment in Ukraine, Poland, Argentina, Colombia, Mexico, Brazil, Guatemala, Portugal, Spain, and India. In the USA, equipment is usually provided by the client; otherwise, you will be expected to use your own setup.
We support continuous growth through personalized development paths tailored to each expert. Also, you can expect:
- An annual learning and development budget
- Internal workshops, tech talks, and mentorship programs
- Opportunities to switch projects or grow into new roles over time
Teams vary by project, but you’ll usually work with a mix of experts across different fields, along with a delivery or project manager who supports collaboration and onboarding.
For day-to-day work, teams commonly use tools like Jira and Google Workspace, along with communication platforms such as Google Chat. Depending on the client, you may also work with Slack, Confluence, Notion, or similar tools.
Need help?
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If something doesn’t work or you have questions regarding your application process, drop us a line.
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