Senior Data Engineer

5 days ago


Gurgaon, Haryana, India Freecharge Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Job Title: Senior Engineering  (Data Engineering)

Location: Gurgaon

Experience Required: 3+ Years

Employment Type: Full-Time

Department: Data & Analytics

About the Role

We are looking for a passionate and experienced Big Data Engineer for driving the design and

development of core platform frameworks with the mega knowledge of Spark, Python/Scala

and Kafka Streams that enable the delivery and construction processes for the Data

Management, Data Discovery and Analytics group, and using emerging big data technologies.

This is a hands-on leadership role requiring both technical expertise and people management skills to guide a growing team and ensure delivery of high-impact data solutions.

Key Responsibilities

  • Gather and process raw data at scale.

    Design and develop data applications using selected tools and frameworks.

    Read, extract, transform, stage, and load data to selected tools and frameworks.

    Build and execute data warehousing, mining, and modeling activities using agile

    development techniques.

    Perform tasks such as writing scripts, calling APIs, writing SQL queries, etc.

    Deploy and monitor products on AWS Cloud platform

    Monitoring data performance and modifying infrastructure as needed.

    Developing ETL flows based on Hadoop/Big Data stack technology: Apache Nifi, Hive,

    Spark, Kafka,AWS GLUE ,AWS LakeFormation,AWS S3.

    Troubleshooting and performance optimization for data processing flows, data models.

    Able to develop and maintain Python based Rest apis.

Required Qualifications

3+ years of Big data development experience with working proficiency in Java/Scala

Python to write data pipelines and data processing layers.

Strong in Data Structures & Algorithms, Analytical, and problem-solving skills.

Proficiency in Python with exposure to any web frameworks.

Proficiency with Spark, Hadoop v2, MapReduce, HDFS.

Experience with building stream-processing systems, using solutions such as Storm, or

Spark-Streaming.

Experience with the integration of data from multiple data sources.

Experience with SQL, NoSQL databases.

Experience with various messaging systems, such as Kafka, or RabbitMQ.

Experience with confluent packages like Kafka connect, schema registry.

Experience with Cloudera/MapR/Hortonworks.

Experience with AWS big data solutions like GLUE,Redshift,Lakeformation.

Experience in Data Lake platforms like Hudi,Iceberg or Delta.

Good knowledge of Big Data querying tools, such as Pig, Hive or Impala

Knowledge of various ETL techniques and frameworks, such as Flume.


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