Job Summary
Key Responsibilities
- Assist in building, testing, and maintaining data pipelines and ETL processes for structured and unstructured data.
- Work with cloud-based data platforms and tools, including database systems, data warehouses, and modern data lakes (e.g., Datasphere, AWS, Azure, or GCP services).
- Collaborate with senior engineers and data analysts to gather requirements, integrate data sources, and optimize data workflows.
- Monitor data quality, ensure proper documentation, and resolve pipeline issues under supervision.
- Participate in code reviews, testing, and deployment to maintain engineering standards and data reliability.
Required Skills
- Knowledge of SQL and basic database concepts.
- Familiarity with programming languages such as Python, Java, or Scala for data manipulation.
- Understanding of ETL concepts and workflow orchestration tools (e.g., Airflow).
- Basic cloud platform knowledge (e.g., AWS S3, Redshift, Google BigQuery) and Dataverses/Datasphere environments.
- Strong analytical and problem-solving skills, with attention to detail.
- Willingness to learn and adapt to evolving data technologies in big data and cloud platforms.
Preferred Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
- Internship or project experience with data pipelines, data transformation, and reporting tools.
- Understanding of data modeling, normalization, and business intelligence concepts.
Key Responsibilities
2. Utilize data analysis techniques to interpret complex data sets and identify trends.
3. Design and implement python scripts for automation and data manipulation.
4. Collaborate within team to gather requirements and deliver high-quality solutions.
5. Participate in code reviews, troubleshoot issues, and optimize application performance.
6. Create data visualizations and reports to present findings to stakeholders.
7. Stay updated on emerging technologies and trends in sql, data analysis, and python.
Skill Requirements
2. Strong knowledge of data analysis techniques and tools.
3. Experience in python programming for software development and automation.
4. Good problem-solving skills and attention to detail.
5. Ability to work effectively in a team environment and communicate technical concepts clearly.