Job Title- Data Analyst
Experience- 6 plus years.
Location- Viman Nagar Pune.
Timings- 11 am- 8 pm.
Be part of AcquireX team that unleashes the power of leading-edge technologies to help improve e-commerce processes in the e-commerce world. We are looking for a
Data Analyst to analyze, transform, and validate data that powers analytics, reporting, and operational decision-making. You will work with multiple data sources and internal systems to ensure data accuracy, consistency, and usability.
Key Responsibilities
- Transform, normalize, and analyze data for business insights and reporting
- Write and optimize SQL queries across analytical databases
- Work with PostgreSQL, MS SQL Server, Redis/Oracle (ClickHouse is a plus)
- Build and maintain analytical datasets using Python and SQL
- Ensure high data quality by identifying duplicates, errors, and inconsistencies
- Create visualizations and dashboards for stakeholders
- Document datasets, metrics, and analysis logic
- Collaborate with engineers, analysts, and business teams
Requirements
- 6+ years of experience as a Data Analyst (or Analytics-focused role)
- EDA (Exploratory Data Analysis)
- Strong SQL skills (joins, aggregations, window functions, optimization)
- Proficiency in Python for data analysis:
- Pandas (must have)
- NumPy (must have)
- Hands-on experience with interactive visualization:
- Plotly (must have)
- Experience working with CSV, JSON, and XML data formats
- Familiarity with GCP and working knowledge of Azure
- Understanding of data normalization and multi-source analysis
- English proficiency: Intermediate
Must Have
- Experience with ClickHouse is a plus
- Familiarity with Dask or Polars for large datasets
- Experience with Matplotlib or Seaborn
- Exposure to scikit-learn, SciPy, or Statsmodels
- Experience with e-commerce analytics or marketplaces
Tech Stack (Core)
- Languages: SQL, Python
- Analysis: Pandas, NumPy
- Visualization: Plotly (primary), Matplotlib / Seaborn (plus)
- Big Data: Dask, Polars
- Databases: PostgreSQL, MS SQL Server, Redis/Oracle, ClickHouse (plus)
- Environment: Jupyter Notebook / JupyterLab, Dash
- Cloud: GCP, Azure (basic)
