Data Engineer Intern, Data Science Intern

Cognira

. Compare Apache Spark and DuckDB on existing transformations to select suitable transformations for migration .

Posted 10/27/2026internshipTunis • TunisiaEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Python and SQL for data analytics and software engineering, with a strong focus on machine learning, deep learning, and time series forecasting. Proficient in utilizing Databricks and PySpark for data transformations and analysis.

Highest-signal resume keywords

PythonSQLMachine LearningDeep LearningDatabricks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsStatisticsSoftware EngineeringTime Series ForecastingPySparkPyTorchLarge Language ModelsDuckDBNatural Language ParsingScala

Tools & Technologies

DatabricksDuckDBPySparkPyTorch

Industry Keywords

Data TransformationForecasting ModelsAI DebuggingBenchmarkingProduct Hierarchies

Tech Stack

Tools & technologies

ApacheCloudPySparkPythonPyTorchScalaSparkSQL

About the role

Key responsibilities & impact

Compare Apache Spark and DuckDB on existing transformations to select suitable transformations for migration
Implement DuckDB versions of selected transformations with automated equivalence tests against Spark versions
Develop and test a way to run DuckDB transformations on Databricks, including compute type, dependencies, and data access
Modify pipeline orchestration so each step declares whether it runs on Spark or DuckDB
Create a command to run DuckDB transformations locally with sample data or cloud storage data
Ensure one code version for each transformation runs locally and on Databricks without changes
Build a science module that groups products into likely complements and substitutes and assembles product hierarchies from product descriptions
Develop a prototype AI debugging agent, its read-only toolset, and an evaluation framework for identifying root causes of forecast differences
Benchmark deep learning forecasting models against production models and analyze when they improve promotional demand forecasting performance

Requirements

What you’ll need

Python
SQL
Data Analytics
Statistics
Software Engineering
Machine Learning
Deep Learning
Time Series Forecasting
Databricks
PySpark
PyTorch
Large Language Models (LLMs)
Please submit your resume in English
Nice to have: DuckDB
Nice to have: Knowledge of LLM techniques
Nice to have: Natural Language Parsing familiarity
Nice to have: Scala
Nice to have: LLM agents

Benefits

Comp & perks

Opportunity to work with a global team
Exposure to retail science, scalable technologies, data engineering, and data science
Internship experience with Cognira's Data Engineering and Data Science teams