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Data Analytics( Python + SQL )

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Onsite

Data Analytics( Python + SQL )

HR India Solutions

Data Analytics( Python + SQL )

Skills

SQL QueriesTableauData MiningPythonNumPypandasData AnalysisOraclePySparkHadoop

20 days ago

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Important information


Contract type:

Permanent

Salary:

₹1,500,000 – ₹2,250,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

30 September 2026

What they need


This role is ideal for someone with strong expertise in SQL, Python, Hadoop/Oracle and Pyspark, and a solid background in data analysis and wrangling.

You will play a key role in building and maintaining analytical solutions that drive insights, especially in the area of fraud detection within card transactions and account opening domains.

Key Responsibilities:

  • Develop, maintain, and optimize complex SQL queries to support data extraction and transformation activities.
  • Utilize Python for advanced data processing, automation, and analytical modeling.
  • Build and maintain Tableau dashboards that provide actionable insights to stakeholders.
  • Perform data wrangling and cleansing from various sources to prepare data for analysis.
  • Conduct detailed data analysis to uncover trends, patterns, and potential fraudulent activity.
  • Collaborate with fraud analytics and operations teams to develop and enhance fraud detection frameworks.
  • Document data processes and maintain data integrity across workflows.
  • Contribute to continuous improvement in data pipelines, tools, and reporting mechanisms.

Required Skills and Qualifications:

  • Proven experience in writing efficient and complex SQL queries for large datasets.
  • Strong programming skills in Python, with knowledge of data libraries such as Pandas, NumPy, etc.
  • Hands-on experience building visualizations and dashboards using Tableau.
  • Experience with data wrangling, cleaning, and transformation techniques.
  • Solid understanding of data analysis methodologies and problem-solving using data.
  • Excellent communication skills and ability to present technical findings to non-technical stakeholders.
  • Attention to detail and commitment to delivering high-quality work.

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