Data Analyst
Thales
Bengaluru, Karnataka, India1h agovia LinkedIn
About the Role
Data Analyst at Thales.
Key Responsibilities
- Implement data validation checks and ensure dataset reliability.
- Support validation/testing for data pipelines (e.g., data checks, unit tests for transformations).
- Design data models and build reliable reporting structures.
- Create dashboards and visualizations using tools like Power BI or equivalent.
- Extract, join, and transform data using SQL.
Requirements & Tech Stack
- Python (and/or SQL) for data analysis.
- SQL for data querying.
- BI/Dashboarding tools (e.g., Power BI or equivalent).
- Relational databases (e.g., PostgreSQL or equivalent).
- Git.
- Agile processes.
Qualifications
- Strong proficiency in Python (and/or SQL) for data analysis.
- Strong expertise in SQL for data querying.
- Good experience designing data models and building reliable reporting structures.
- Good experience with dashboarding/visualization tools (e.g., Power BI or equivalent).
- Solid understanding of descriptive statistics and key analytical methods (segmentation, trends, correlations, basic inference).
- Experience implementing data validation checks and ensuring dataset reliability.
- Good experience working with relational databases such as PostgreSQL (or equivalent).
- Experience supporting validation/testing for data pipelines (e.g., data checks, unit tests for transformations).
- Autonomy, technical excellence, clear communication, teamwork, problem-solving, adaptability, curiosity, and continuous improvement.
- Familiarity with software/data lifecycle concepts and tools such as Git and Agile processes.
Desired Skills:
- Experience with data warehouses/lakehouses (e.g., Snowflake, Databricks, or similar).
- Experience with time-series analysis, forecasting, or causal impact methods.
- Good experience in preparing technical documentation for datasets, metrics, and analytical workflows.
- Good experience with CI/CD for data pipelines and GitLab CI/CD.
- Experience integrating LLM/AI-enabled analytics (e.g., automated insight generation, structured reporting, or enhanced querying) if applicable to the environment.