Lead Data Analyst (SQL +Pyspark +ETL pipelines)
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Job Location:
Monthly Salary:
Posted on:
5 days ago
Vacancies:
1 Vacancy
Job Summary
Job Summary
We are looking for an experienced Data Analyst (ETL & Analytics) with strong expertise in SQL ETL execution data validation and pipeline diagnostics. The role involves executing and monitoring pre-built ETL workflows performing data integrity checks supporting technical issue resolution and delivering structured insights to stakeholders. The ideal candidate should be comfortable working in Agile environments with SOP-driven processes and handling multiple data requests efficiently.
Key Responsibilities Experience
ETL Execution & Data Analytics - 6 8 years of experience in data analysis with strong focus on ETL execution and data pipeline management.
- Proven ability to validate large datasets interpret model outputs and detect anomalies quickly.
- Experience in preparing executive-ready analytical summaries presentations and data quality reports.
- Collect review and validate required data inputs for analysis (target lists segments deciles forecasts promotional datasets etc.).
- Execute pre-built ETL models and pipelines following Agile methodologies and standard operating procedures (SOPs).
- Perform detailed data diagnostics to ensure data integrity pipeline stability and output accuracy.
- Identify and resolve pipeline failures or data issues including crisis handling and technical project coordination.
- Provide structured recommendations based on analytical findings in collaboration with stakeholders.
- Create documentation and analytical summaries to communicate pipeline diagnostics and results effectively.
- Partner with project stakeholders to align technical outputs with business objectives.
- Coordinate with cross-functional teams to support smooth execution of deliverables.
- Maintain issue logs diagnostic summaries and clear reporting to ensure transparency and faster decision-making.
- Identify opportunities for process improvement standardization and reusable components across ETL pipelines.
- Support prioritization of data requests based on impact timelines and budget considerations.
- Provide responsive support for ad-hoc data runs and evolving analytical requirements.
- Advanced proficiency in SQL for complex querying and data manipulation.
- Basic to intermediate exposure to PySpark for large-scale validation and analysis (preferred).
- Strong experience in working with ETL pipelines and data processing workflows.
- Familiarity with Agile delivery models and structured technical SOP environments.
- Understanding of pipeline optimization and performance tuning concepts.
