Data Analyst

at  CAPGEMINI ENGINEERING

DATA ANALYST - WORK FROM HOME

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Location: Colombia
We are seeking a Data Analyst with 2+ years of experience using SQL and Python to analyze and interpret large datasets. The ideal candidate will have experience working with massive data volumes (over 1 billion records) and be familiar with data processing tools such as Spark, Presto, and Athena. You will play a key role in analyzing data, deriving business insights, and effectively presenting findings to help drive business decisions.
Key Responsibilities:
Use SQL and Python to extract, manipulate, and analyze large datasets for solving complex business problems.
Work with large data sets, often exceeding 1 billion records, using tools like Spark, Presto, and Athena for efficient data processing and analysis.
Clean, transform, and prepare data for analysis, ensuring high data quality and integrity.
Design and implement data pipelines for automating data extraction, transformation, and loading (ETL).
Create and maintain data models that allow for easy access and analysis of business data.
Collaborate with cross-functional teams (e.g., business analysts, product managers, and stakeholders) to understand business requirements and provide data-driven insights.
Develop dashboards and reports to present findings and support decision-making processes.
Communicate complex technical concepts and insights in a clear and accessible manner to both technical and non-technical stakeholders.
Tell a compelling data story, translating numbers and trends into actionable insights that drive business strategy.
Required Skills & Qualifications:
2+ years of experience working with SQL and Python for data analysis and reporting.
Experience working with large data sets (more than 1 billion records), and proficiency with tools like Spark, Presto, and Athena for handling and processing big data.
Strong knowledge of data analysis techniques, including statistical analysis, data cleaning, and visualization.
Proficient in data wrangling and transforming data into actionable insights.
Solid understanding of ETL processes and experience working with data pipelines.
Strong communication skills to present data findings to stakeholders in a clear and concise manner.
Ability to tell a story with data, connecting insights to real-world business problems and opportunities.
Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
Preferred Skills:
Experience with cloud-based data platforms (e.g., AWS, Google Cloud, Azure).
Knowledge of machine learning and predictive analytics (Python libraries such as Pandas, Scikit-learn, TensorFlow).
Familiarity with data warehousing concepts and tools.
Strong problem-solving and critical-thinking skills.
Ability to work independently and collaboratively within a fast-paced environment.

Please refer the Job description for details