Neha Bhakare

Data Scientist

Pune, Maharashtra, India4 yrs 2 mos experience

Highly Stable

Key Highlights

Expert in SQL-driven data analysis and reporting.
Proven track record in optimizing ETL processes.
Strong collaboration with stakeholders for data accuracy.

Stackforce AI infers this person is a Data Analyst with expertise in ETL processes and data visualization in SaaS environments.

Contact

Skills

Core Skills

Data AnalysisSqlEtl/eltData Visualization

Other Skills

Agile MethodologiesAgile Project ManagementAmazon S3Azure Data FactoryAzure Data LakeAzure DatabricksBootstrapBusiness Requirements gathering & documentationC (Programming Language)Cascading Style Sheets (CSS)ConfluenceCore JavaCreative WritingData GovernanceData Modeling

About

Senior Data Analyst with nearly 4 years of experience in SQL-driven data analysis, data validation, and governance-focused analytics across regulated domains. Strong hands-on expertise in writing complex SQL queries, implementing data quality checks, and translating business requirements into accurate, reliable reports. Experienced in working with structured datasets, supporting data engineering workflows, and collaborating closely with business stakeholders to ensure data accuracy, reconciliation, and audit readiness. Adept at delivering analytics and reporting solutions in consulting and client-facing environments using SQL, Python, and Power BI.

Experience

Ascendion

Senior Data Analyst

Jul 2025 – Present · 8 mos · Pune, Maharashtra, India · Hybrid

Client - ZS associates

SQLData ValidationData GovernanceData AnalysisReporting

Infosys

3 roles

Senior System Engineer

Promoted

Apr 2024 – Jul 2025 · 1 yr 3 mos

With 3yrs of experience as data analyst, performed development, testing and troubleshooting of ETL/ELT development projects, PySpark, SQL.
Despite consuming batch and streaming big data from different separate data sources, a data pipeline uptime of 99.8% was maintained with the assistance of Spark, Python, Azure data factory.
Designed and constructed efficient ETL data pipelines solutions utilizing, allowing for smooth data processing and analysis. Optimization strategies reduced data processing time by 20%, enhancing overall efficiency.
Used Azure significantly for scalable data processing and storage, including Databricks, Data Lake Storage Gen2 . Utilized Agile methodologies, participated in testing, code reviews, build release and other weekly meetings with staff and partners.
Auto-scaling was implemented, lowering infrastructure costs by 25% and optimizing resource allocation.
Migrated codebase to PySpark using azure Databricks, which increased performance and scalability by 55%.
Improved system performance by optimizing existing code for efficient data processing.
Developed Power BI dashboards with improved efficiency via efficient data retrieval and better caching, delivering visuals and important insights to stakeholders.
Delta Lake tables were implemented to provide effective data versioning, management, and data quality control in data lakes. Improved data consistency and dependability by adopting data validation checks, which reduced data discrepancies by 27%.
Collaborated with cross-functional teams to understand data requirements and design efficient ETL/ELT processes. Implemented and maintained data pipelines with knowledge of Spark streaming & query optimisation.