Hadoop Developer || Jersey City, NJ/Phoenix, AZ/Seattle, WA/Dallas, TX (Onsite) || FTE with TCS

Veridian Tech View all jobs
Jersey City, NJ, United States
24 days ago
Apply on www.careerjet.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours

Tech stack

Java (Programming Language) Cloudera Impala Information Engineering Extract Transform Load (ETL) Apache Hadoop Hadoop Distributed File System Apache Hive Python (Programming Language) Performance Tuning Scala (Programming Language) SQL Databases Apache Yarn
+4 more
Data Lakes Pyspark Data Management Stream Processing

Requirements

Required Hard and Soft Skills / Experience Deep Expertise in PySpark, including performance tuning and optimization Strong python development experience in large-scale distributed environment Solid knowledge of Hadoop ecosystem (HDFS,Hive/Impala, YARN) Proven experience designing and governing enterprise, regulatory facing data platforms. Expertise in designing data lakes, ELT/ETL pipelines, batch and real time data processing solution Proficiency in programming languages such as Java, Scala and SQL Strong understanding of non-functional requirements and production support models Clear written and verbal communication skills with ability to influence across organizations, Job Title: Senior Developer Location: Charlotte, NC Full-Time Job Description Must Have Technical/Functional Skills Primary Skill: Data Engineering, Platform Engineering …

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerjet.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:41 min

Visualizing the complex developer journey for JVM ecosystems

Bobur Umurzokov · LIVE

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

3:24 min

The governance failures of centralized data lakes

Mario Meir-Huber · LIVE

6:24 min

Distributed data lakes and containerized computing clusters

Ulrich Wurstbauer +1 · LIVE

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

3:37 min

Scaling machine learning pipelines from prototypes to petabytes

Julian Joseph · LIVE

Videos

See all

Related articles

See all