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Known employer, Bengaluru metro, and mid-level generalist data role increases applicant competition.
Core skills (AWS, Spark, Python, ETL) are broadly transferable across industries, so low domain bias.
Explicit 5–10 years plus mandatory AWS, Python, Spark, Databricks and data engineering skills enforce strict filtering.
Analyze large-scale datasets to uncover trends, anomalies, and actionable insights that drive organizational decisions.
Design, build, and optimize data pipelines and analytical models using AWS services and potentially Databricks to improve data infrastructure and workflows.
Identify system inefficiencies and propose scalable architectural improvements focused on performance, reliability, cost-effectiveness, and data quality.
5–10 years of experience in data analysis, engineering, or related data-driven roles.
Strong hands-on expertise with AWS ecosystem and proficient in Python for building scalable data pipelines and analysis workflows.
Experience in data science or analytics with 3–5 years including statistical analysis and applied machine learning techniques.
Exposure to Databricks is strongly preferred; Advanced degree is nice to have but not mandatory.
Experienced in distributed data processing frameworks (e.g., Spark, EMR, Glue, Databricks) and system design in cloud environments.
Demonstrated ability to detect systemic inefficiencies and optimize infrastructure for large-scale data workflows in AWS.
Skilled in translating complex analytical insights into scalable engineering solutions supporting business and operational improvements.