Databricks Data Analyst

Role Overview

data exploration

Location:

Key Responsibilities

Data Analysis & Reporting

• Perform data extraction, transformation, and analysis using Python/PySpark, Databricks and SQL.
• Utilize advanced Excel functionalities to manipulate and analyze large datasets, create reports, and generate actionable insights.
• Develop and validate dashboards and reports to present actionable insights to business teams.
• Perform ad-hoc analysis to support business decisions, identify opportunities for process improvement, and optimize operational performance.
• Conduct thorough data validation and reconciliation to ensure consistency and reliability of reporting metrics
• Proactively identify data discrepancies, anomalies, and trends, and recommend corrective actions as needed
• Validate data accuracy and consistency across multiple sources.

Collaboration

• Work closely with data engineers to ensure availability of clean, curated datasets.
• Work with team leads and business stakeholders to understand business requirements and translate them into data-driven solutions
• Support ad-hoc analysis for strategic initiatives
• Collaborate with cross-functional teams to streamline data processes, enhance data quality, and drive organizational efficiency.
• Provide training and support to end-users on data tools and techniques, empowering them to leverage data effectively

Optimization & Governance

• Ensure compliance with data governance and security standards.
• Optimize queries for performance and cost efficiency.
• Maintain documentation for datasets, reports, and analytical processes.

Required Skills & Experience

• 3–5 years of experience in data analysis or business intelligence.
• Hands-on expertise in:

• Databricks

  (PySpark, Spark SQL, Delta Lake)

• Excel, and SQL

  for data querying and analysis

• BI tools

  (Power BI, or similar)

• Python

• Strong analytical, communication, problem-solving, and visualization skills with attention to detail.

Preferred Qualifications

• Knowledge of AWS services (S3, RDS) for data access.
• Experience with large datasets and distributed computing environments.
• Exposure to AI/ML concepts for advanced analytics (advantage).