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Data Engineer

Data Engineer

Rmsi

2 - 5 years

9 - 15 Lacs

Noida

Posted:2 weeks ago| Platform:

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Skills Required

Data Engineering Python SQL

Work Mode

Work from Office

Job Type

Full Time

Job Description

Position Overview

Data Engineer

Key Responsibilities

Automate data collection from sources such as NOAA, ECMWF, IMD, NASA, and regional hydrological agencies.
Process and clean large datasets, ensuring data integrity, accuracy, and accessibility.
Handle large-scale geospatial and time-series datasets related to rainfall, river discharge, groundwater levels, and climate models.
Work with climate projection datasets (e.g., CMIP6, ERA5) for impact assessments and forecasting.
Develop efficient storage solutions using cloud platforms (AWS, GCP, or Azure).
Support hydrological and hydraulic modeling teams by structuring input data for flood simulations, drought analysis, and climate impact assessments.
Collaborate with data scientists to build machine learning models for climate risk assessment.
Implement scalable data processing workflows using Python, SQL, and distributed computing tools.
Optimize data workflows for efficient processing and visualization.
Work closely with hydrologists, climate scientists, and engineers to understand data requirements.
Document data pipelines, metadata, and workflows for reproducibility and transparency.

Required Qualifications & Skills

Education & Experience

Bachelors or Masters degree
in Computer Science, Data Science, Environmental Engineering, Hydrology, Climate Science, or a related field.
3-5 years
of experience in data engineering, preferably in climate science, hydrology, or environmental domains.

Technical Skills

Strong programming skills in
Python, SQL, or R
.
Experience with
big data processing tools
(Apache Spark, Dask, or Hadoop).
Familiarity with
climate and hydrological datasets
(HECRAS, HEC HMS, SWAT, GFS).
Experience with
geospatial data tools
(GDAL, PostGIS, GeoPandas).
Knowledge of
cloud platforms
(AWS S3, GCP BigQuery, Azure Data Lake).

Preferred Skills

Experience in
climate risk modeling
and statistical analysis of environmental data.
Familiarity with APIs for climate data access (Copernicus, NASA Earthdata).
Understanding of
hydrological models
and
remote sensing datasets
.

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