Data Engineer

DemandMatrix

India

On-site

INR 2,000,000 - 3,000,000

Full time

14 days+

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Job summary

A leading data analytics firm in India is seeking a Director-level Data Engineer to oversee the architecture and maintenance of large-scale big data platforms. Candidates should have over 7 years of relevant experience and expertise in technologies like Apache Hadoop and PySpark. This full-time position offers a chance to work with cutting-edge data processing systems and drive innovation in data analytics.

Qualifications

7+ years of experience architecting, developing, releasing, and maintaining large-scale big data platforms.
5+ years proficiency in configuring and deploying applications on Linux-based systems.
Expertise with data processing systems including streaming, event, and batch.

Responsibilities

Oversee the development and maintenance of big data platforms.
Implement data processing models and optimize feature extraction.

Skills

Apache Hadoop

PySpark

Python

Design patterns

Data Structures and Algorithms

Job description

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This range is provided by DemandMatrix. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Only a solid grounding in computer engineering, Unix, data structures and algorithms would enable you to meet this challenge.
7+ years of experience architecting, developing, releasing, and maintaining large-scale big data platforms on AWS or GCP.
Understanding of how Big Data tech and NoSQL stores like MongoDB, HBase/HDFS, ElasticSearch synergize to power applications in analytics, AI and knowledge graphs.
Understanding of how data processing models, data location patterns, disk IO, network IO, shuffling affect large scale text processing - feature extraction, searching etc.
Expertise with a variety of data processing systems, including streaming, event, and batch (Spark, Hadoop/MapReduce).
5+ years proficiency in configuring and deploying applications on Linux-based systems.
5+ years of experience Spark - especially Pyspark for transforming large non-structured text data, creating highly optimized pipelines.
Experience with RDBMS, ETL techniques and frameworks (Sqoop, Flume) and big data querying tools (Pig, Hive).

Stickler of world class best practices, uncompromising on the quality of engineering, understand standards and reference architectures and deep in Unix philosophy with appreciation of big data design patterns, orthogonal code design and functional computation models.