Nilima Bhosale

Software Engineer

Navi Mumbai, Maharashtra, India4 yrs 10 mos experience

Key Highlights

Designed over 10 scalable data pipelines.
Improved data reliability by 30-40%.
Delivered KPI dashboards for data-driven decisions.

Stackforce AI infers this person is a Data Engineer specializing in scalable data pipeline solutions for analytics.

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Skills

Core Skills

Data EngineeringEtlData AnalysisData Management

Other Skills

Apache NiFiAirflowPySparkHiveHadoopNiFiCI/CDAzure DevOpsKPI DashboardsSQLPython (Programming Language)DatabricksMedallion ArchitectureDelta LakeDLT

About

I’m a Data Engineer with around 3 years of experience designing and implementing scalable, end-to-end data pipelines using Apache NiFi, Airflow, PySpark, Hive, Hadoop, and SQL. I’ve built reliable batch and near real-time workflows across security and retail analytics domains, working on platforms like Cloudera CDP and Hortonworks HDP. My work includes orchestrating complex data pipelines, optimizing PySpark jobs, and ensuring smooth ETL/ELT processes for structured and semi-structured data. I’ve also contributed to business-critical dashboards using Zoomdata, turning raw data into actionable KPIs. I focus on performance tuning, cost optimization, and seamless deployments using CI/CD and Azure DevOps, consistently improving data quality and operational efficiency. If you're hiring Data Engineers or looking to strengthen your data capabilities, I’d love to connect!

Experience

4 yrs 10 mos

Total Experience

1 yr 5 mos

Average Tenure

5 mos

Current Experience

V4c.ai

Senior Data Engineer

Jan 2026 – Present · 5 mos · Hyderabad, Telangana, India

Apache NiFiAirflowPySparkHiveHadoopData Engineering+1

Jio platforms limited (jpl)

Data Engineer

Mar 2023 – Jan 2026 · 2 yrs 10 mos · Navi Mumbai, Maharashtra, India · On-site

Designed and deployed 10+ end-to-end data pipelines using NiFi, Airflow, PySpark, Hive, and Hadoop, improving data reliability and reducing latency by 30 to 40 percent across security and retail analytics.
Built and optimized PySpark and Hive jobs for large structured and semi-structured datasets, improving pipeline performance by up to 25 percent and automating key ETL processes.
Developed near real-time ingestion workflows and automated orchestration with Airflow, reducing manual effort by 50 percent and improving on-time pipeline completion.
Delivered KPI-focused analytics dashboards and implemented CI/CD with Azure DevOps, reducing deployment time by 50 percent and enabling faster, data-driven decisions.

NiFiAirflowPySparkHiveHadoopCI/CD+4