[Job-29268] Data & Analytics Engineer, Colombia

• Exploratory Data Analysis (EDA):

  • Conduct EDA and statistical profiling to identify trends and insights from data.
  • Perform feature engineering specifically for time-series forecasting.

• Data Wrangling and Preparation:

  • Extract and transform data from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats.
  • Develop pipelines for data ingestion and processing.

• Machine Learning Modeling:

  • Build classical ML models for time-series forecasting, regression, and capacity/throughput modeling.
  • Evaluate model performance using metrics such as RMSE, MAE, and MAPE, documenting performance results.

• Data Visualization:

  • Create insightful data visualizations and dashboards using Amazon QuickSight or equivalent BI tools.

• Python Data Stack:

  • Utilize the Python data stack (pandas, NumPy, scikit-learn, matplotlib/seaborn) for data manipulation and analysis.

• Model Explainability:

  • Apply SHAP or other model explainability techniques to interpret model outputs.

• Collaboration and Communication:

  • Work closely with stakeholders to translate business rules into effective feature engineering pipelines.
  • Engage in milestone-driven, Firm Fixed Price delivery models, ensuring timely project completion.

Requirements for this challenge:

• 4+ years in data engineering or applied data science roles, preferably with experience on AWS.
• Proficient in exploratory data analysis (EDA), statistical profiling, and feature engineering for time-series forecasting.
• Experience in data wrangling from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats.
• Strong understanding of classical ML modeling techniques, including time-series forecasting and regression.
• Familiarity with model evaluation metrics (RMSE, MAE, MAPE) and performance documentation.
• Experience in data visualization and dashboard development using Amazon QuickSight or equivalent BI tools.
• Hands-on experience with Amazon SageMaker (training, evaluation, Clarify).
• Proficient in the Python data stack, including pandas, NumPy, scikit-learn, matplotlib, and seaborn.
• Working knowledge of SQL and dimensional modeling.
• Familiarity with SHAP or model explainability techniques is a plus.

Expected Certifications

• AWS Certified Cloud Practitioner
• AWS Certified Data Engineer – Associate
• AWS Certified Machine Learning – Associate or AWS Certified Machine Learning – Specialty

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Our benefits include:

- Premium Healthcare

- Meal voucher

- Maternity and Parental leaves

- Mobile services subsidy

- Sick pay-Life insurance

- CI&T University   

- Colombian Holidays

- Paid Vacations

And many others. 

Collaboration is our superpower, diversity unites us, and excellence is our standard. 

We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.