Omkar Lahare

Data Engineer

Pune, Maharashtra, India2 yrs 11 mos experience
Highly Stable

Key Highlights

  • Engineered ETL pipelines processing 1 TB of data daily.
  • Enhanced Spark performance by 40% through optimization.
  • Improved customer retention by 20% with data-driven strategies.
Stackforce AI infers this person is a Big Data Engineer specializing in Telecom and Banking Analytics.

Contact

LinkedIn

Skills

Core Skills

Big Data & Distributed ProcessingData Ingestion & Orchestration

Other Skills

HadoopApache NiFiSqoopApache HiveSnowflakeApache SparkAWSAWS GlueGitHubMySQLPostgreSQLApache KafkaShell ScriptingLinuxScala

About

✨ About 🚀 Results-driven Big Data Engineer with a proven track record in designing and implementing scalable, high-performance data pipelines across telecom, banking, and analytics domains. I specialize in transforming massive datasets (1 TB+ daily) into actionable insights by leveraging modern big-data and cloud technologies. 🔧 Core Expertise Big Data & Distributed Processing: Apache Spark (PySpark/Scala), Spark SQL, HDFS, YARN, MapReduce Data Ingestion & Orchestration: Apache Airflow, Sqoop Data Warehousing & Analytics: Apache Hive, Snowflake, Redshift Programming & Automation: Python, Scala, Shell Scripting, Linux, Git, CI/CD Workflows Cloud Platforms: AWS (S3, Glue, EMR, Lambda, Redshift, SNS , IAM ) 📈 Key Achievements Engineered and deployed end-to-end ETL pipelines processing over 1 TB of data daily from CRM, billing, and network sources. Enhanced Spark performance by 40% through partitioning, caching, and query optimization. Delivered analytical solutions for ARPU, CLTV, and Churn—empowering data-driven marketing strategies and improving customer retention by 20%. 💡 I’m passionate about building reliable, scalable, and automated data systems that bridge the gap between raw data and business intelligence. I love solving complex data challenges and thrive in environments where data engineering drives real business value. 📬 Let’s connect to discuss data architecture, big data performance optimization, and cloud-native data engineering best practices.

Experience

2 yrs 11 mos
Total Experience
2 yrs 11 mos
Average Tenure
2 yrs 11 mos
Current Experience

Confidential

Data Engineer

Jun 2023 – Present · 2 yrs 11 mos · Maharashtra, India

  • Possessing in-depth knowledge of Hadoop and its internals, I have worked extensively on building and optimizing large-scale distributed data processing systems for real-world business needs.
  • 💡 My expertise spans across the entire data engineering lifecycle — from ingestion and processing to storage and analytics.
  • 🔹 Data Ingestion & Integration: Proficient in Apache NiFi and Sqoop, enabling seamless movement of data between RDBMS and big-data environments.
  • 🔹 Data Warehousing: Experienced in Apache Hive and Snowflake, implementing partitioning, bucketing, and schema optimization for efficient query performance.
  • 🔹 Data Processing: Strong command over Apache Spark (Scala), leveraging DataFrames, Datasets, and Spark SQL to build high-performance ETL pipelines and perform large-scale transformations.
  • 🔹 Cloud Platforms: Skilled in AWS (EMR, S3, Glue, Redshift) — orchestrating and automating data workflows in cloud-native architectures.
  • 🔹 Problem-Solving & Delivery: Known for designing and deploying end-to-end pipelines that process terabytes of data daily, reducing latency and improving reliability across multiple projects.
  • I take pride in turning raw data into actionable insights through clean, scalable, and production-ready architectures. My strength lies in debugging complex systems, optimizing performance, and ensuring smooth, automated data operations in both on-premise and cloud environments.
HadoopApache NiFiSqoopApache HiveSnowflakeApache Spark+3

Education

Government College of Engineering And Research,Pune

Bachelor of Engineering - BE

Jul 2019 – Jul 2023

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