Data Analyst / Power BI Developer

01-Dec-2025

CHENNAI

Graduation in Engineering

3 Years - 0 Months To 4 Years - 0 Months

Core Data & Analytics Skills
Strong proficiency in data analysis, data modeling, and visualization techniques. Solid experience in SQL (joins, CTEs, stored procedures, performance tuning). Knowledge of ETL/ELT processes and data transformation methods. Ability to work with both structured and unstructured data. Understanding of data warehousing concepts (Star Schema, Snowflake Schema, OLAP vs OLTP). Strong business acumen to translate requirements into analytical solutions. Power BI Expertise Proficiency in building interactive dashboards and reports using Power BI Desktop and Power BI Service. Expertise in DAX (Data Analysis Expressions) and Power Query (M Language). Designing and implementing data models, measures, and calculated columns. Experience with Row-Level Security (RLS) and data governance. Scheduling, publishing, and maintaining reports/datasets in Power BI Service. Connecting Power BI with multiple data sources (databases, APIs, cloud storage, Excel, SharePoint, etc.). Performance optimization of datasets, queries, and reports.

Strong analytical, technical and domain skills, high conceptual problem-solving mindset, high level of comfort in dealing with high volume.
Demonstrated experience with techniques, programming, and tools relevant to Meta data mapping and analysis including a high level of proficiency with large databases/data warehouse (Oracle, Teradata) and tools such as SAS / SQL. Experience with SQL and ability to write complex queries Experience in supporting data modeling, ETL development, data warehousing, data pipeline and data lake creation projects Experience with cloud infrastructure, data ingestion, data wrangling and visualization tools for Oracle/Azure/GCP/AWS Ability to articulate business problem statement into technical requirements Data Analysis, Data Profiling, Data Management skills Use automated tools to extract/acquire data from primary or secondary data sources Provide quality assurance of imported data. Filter and “clean” Data by reviewing reports and performance indicators to identify and correct problems. Support initiatives for data integrity and normalization Perform Exploratory Data Analysis to assess and interpret meaning of data. Scrutinize data to recognize and identify trends, and patterns. Use statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction Assess and compare Financial and Operational metrics across time periods at Enterprise, regional, and segments level Generate reports from single or multiple systems in various formats, including interactive dashboards, Excel, Ppt, and others Prepare final analysis reports for the stakeholders, enabling them to take important decisions based on various facts and trends Monitor performance and identify improvements Work with different functional teams, and business management heads to identify improvement opportunities Train end-users on new reports and dashboards Demonstrated experience in handling large data sets and relational databases Problem-solving skills. Accuracy and strong attention to detail Demonstrated analytical expertise, including the ability to synthesize complex data Understanding client needs and ability to present findings effectively to stakeholders Experience with statistical methods: Correlation, Regression Analysis, Factor Analysis, Cluster analysis, Decision Trees, etc. Knowledge of how to create and apply the most accurate algorithms to datasets to find solutions is a plus Ability to collaborate effectively and work as part of a team Strong verbal and Written communication skills. Proficiency in statistics and statistical packages like Excel, Python, R, SPSS, or SAS to be used for data set analyzing (Preferred) Knowledge of programming languages like SQL, or ETL frameworks. (Preferred) Knowledge of data visualization software like Tableau, Power BI, etc. Knowledge in AWS/Azure - Data Warehousing concepts (Data Lake / Azure Data Factory / Azure Synapse)