Marab Nitish

CTO

Bengaluru, Karnataka, India10 yrs 7 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Big Data solutions and architecture.
Proven track record in data migration projects.
Strong skills in performance evaluation of new technologies.

Stackforce AI infers this person is a Data Engineering expert with a focus on Big Data solutions and cloud technologies.

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Skills

Core Skills

Bigdata/hadoopSpark/scalaBig DataData Warehousing

Other Skills

Google cloud platformBigQueryHivePysparkSqoopOozieKafkaPythonSQLclickhouseApache AirflowApache SupersetTeradataData WarehouseBusiness Intelligence

About

Sr Data Engineer - Experienced in BigData/Hadoop, Spark/Scala, Spark Stream processing, Google cloud platform, BigQuery, Hive, Pyspark, Sqoop, Oozie, Kafka, Python, SQL, clickhouse, Apache Airflow, Apache Superset , Teradata, Data Warehouse.

Experience

10 yrs 7 mos

Total Experience

5 yrs 3 mos

Average Tenure

8 yrs 1 mo

Current Experience

Target

2 roles

Lead data engineer

Promoted

Apr 2025 – Present · 1 yr 2 mos · Hybrid

BigData/HadoopSpark/ScalaGoogle cloud platformBigQueryHivePyspark+10

Senior Data Engineer

May 2018 – Apr 2025 · 6 yrs 11 mos · Hybrid

Skilled in design, development and implementation of Big Data, Business Intelligence and Data Warehousing Projects.
Programming code independently for intermediate to complex modules following development standards; planning and conducting code reviews for changes and enhancements that ensure standards compliance and systems inter-operability.
Big Data Solution Architect: capable of managing the full lifecycle of Hadoop Solution which includes conducting the requirements analysis, the platform selection, design of the technical architecture, design of the application and development, testing, and deployment of the proposed solution.
Getting the new platform ready, working on the PoC for a smooth transition into the migration projects for different platforms like Teradata to Hadoop to Hadoop3 and from SQL to Hive to Spark-Scala.
Continuous performance evaluation of new technologies like Trino, Clickhouse, Apache Superset, Apache Airflow, External vs Managed hive table, Kafka stream processing and migrating to new technology to beat the previous SLA and keep tuning the flows in production.

Big DataBusiness IntelligenceData WarehousingHadoopSpark-ScalaTeradata+8