Senior Data Engineer

MSCI Inc. is seeking a Senior Data Engineer in New York, NY (onsite) to help deliver reliable climate risk data and analytics. In this role, you will support the ingestion of climate risk and ancillary datasets, build geospatial data pipelines, and apply geospatial and statistical methods to improve risk assessment quality.

Role focus

You will work across processing and interpretation of geospatial observations and modeling data. The role includes integrating databases and pipelines with APIs and web services, implementing quality assurance and quality control for climate risk data and derived statistics, and supporting customer issue resolution with clear model and risk-statistics explanations.

Responsibilities

• Provide technical support for the processing, analysis, and interpretation of geospatial observations and modeling data.
• Develop and implement processes to handle large volumes of hazard prediction data to improve risk assessment quality and accuracy.
• Plan and execute workflows on local and cloud-based environments using tools such as GDAL, PostgreSQL, Python, and Spark.
• Analyze raster and vector data at scale to improve model accuracy, identify quality control issues, and propose remedies.
• Perform statistical analysis to validate hazard model predictions and assess model uncertainties.
• Design and implement quality assurance checks for climate risk data and derived statistics.
• Assist with resolution of customer support issues using quality control checks and explanations of models and risk statistics.

Requirements

• Bachelor’s Degree in Data or Climate Science, or a related field.
• 5+ years of professional experience.
• Experience designing and using databases, such as PostgreSQL.
• Proficiency with SQL queries to analyze complex datasets in an efficient and reproducible way.
• Additional language experience such as Python.
• Experience writing software to process and analyze geospatial data with open source tools.
• Strong understanding of probability and statistics as applied to spatial data.
• Expertise using scripted languages to build data pipelines on local and cloud-based systems.
• Proficiency with source control platforms such as Git.
• A science-based approach emphasizing reliability, accuracy, and reproducibility.
• Experience with GIS and/or geospatial statistical analysis.
• Nice to have: experience with DBT and Spark.

Technologies

• GDAL
• PostgreSQL
• Python
• Spark
• SQL
• Git
• DBT

Compensation and benefits

• Salary range: $125,000 - $163,000 per year, plus eligibility for an annual bonus.
• Transparent compensation schemes and comprehensive employee benefits tailored to your location to support financial security, health, and overall wellbeing.
• Flexible working arrangements, advanced technology, and collaborative workspaces.
• A high-performance, innovation-oriented culture with experimentation and shared responsibility for results.
• A global network of colleagues who share expertise to innovate and deliver for clients.
• Global Orientation program, access to Learning@MSCI, AI Learning Center, LinkedIn Learning Pro, and tailored learning opportunities.
• Multi-directional career paths supported by internal mobility and expanded roles.
• An environment that fosters inclusion and connection, including eight Employee Resource Groups.

What will make you stand out

• Previous experience in the physical sciences.
• Master’s Degree preferred.

Team and role overview

This is a Senior Data Engineer position supporting the Data Operations team. The successful candidate will ingest climate risk and ancillary data from First Street modelers and data partners, develop pipelines, query geospatial databases, compute applicable statistics, and implement Quality Assurance and Quality Control processes. You will also help ensure databases and pipelines coordinate and synchronize with APIs and web services while leveraging geographical imagery to support the First Street mission.