Mapr Engineer Jobs

1 job found

1d ago

Sr Hadoop+Spark(scala) Data Engineer

Virtues Irving, TX

Irving, TX

1d ago

$101k - $110k/yr Full time Senior Big Data Bigdata

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Job Description

Virtues presents an onsite senior Big Data Engineer role in Irving, TX with a competitive annual salary range of $100,696.26 to $110,268.61. This position centers on designing, developing, and supporting scalable batch and real-time data pipelines across multiple data platforms. You’ll work in a collaborative environment to shape data infrastructure and drive data-driven decisions, tackling complex challenges with the Hadoop ecosystem and Spark at scale.

Responsibilities

Design, develop, implement, and maintain scalable, high-performance data ingestion and processing pipelines using Hadoop ecosystem technologies.
Develop and manage data pipelines supporting batch, real-time, streaming, and event-driven processing, including Kafka events.
Read data from structured, semi-structured, and unstructured sources.
Ingest batch data and real-time event streams, including Kafka events.
Perform complex data validation, cleansing, enrichment, and transformation.
Deliver processed data to target data stores, curated data layers, publishing zones, and downstream endpoints.
Develop and optimize Apache Spark applications using Scala for large-scale distributed data processing.
Design and implement Kafka-centric event processing and real-time data pipelines.
Develop streaming data transformation logic using Apache Spark Streaming and/or Spark Structured Streaming.
Build and maintain scalable batch processing solutions using Apache Spark.
Develop data processing and analytical solutions using HiveQL, Pig Latin, HBase, and custom MapReduce programs.
Transform and move data from raw zones to curated and published data warehouse layers.
Collaborate with data architects, application teams, business stakeholders, and platform teams to translate requirements into scalable solutions.
Work extensively with Hadoop technologies including HDFS; MapReduce; Hive; Pig; Sqoop; HBase; ZooKeeper; Oozie; Apache Spark; Scala; Flume/Flume NG; Kafka; Hue.
Apply knowledge of Hadoop architecture and core components such as NameNode, DataNode, HDFS, JobTracker, TaskTracker, and MapReduce programming.
Install, configure, integrate, and support Hadoop ecosystem components within Cloudera-based environments.
Ensure scalability, reliability, fault tolerance, and high performance for distributed storage and processing frameworks.
Monitor and optimize data pipeline performance, resource utilization, throughput, and processing efficiency.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical discipline.
7+ years of hands-on experience with Hadoop framework and the broader Hadoop ecosystem.
6+ years of hands-on experience developing data ingestion and integration solutions across multiple data platforms.
5+ years of strong hands-on experience in Apache Spark with Scala-based distributed data processing.
5+ years of experience in data modeling, data transformation, detailed technical design, and data integration.
Strong experience designing and developing large-scale batch and real-time data pipelines.
Strong experience with HiveQL, Pig Latin, HBase, and custom MapReduce programming.
Experience developing and managing Kafka-centric event-driven data pipelines.
Strong understanding of batch processing, stream processing, and event-driven architecture.
Hands-on experience with Spark Streaming and/or Spark Structured Streaming.
Experience installing and configuring Cloudera Hadoop ecosystem components, including Hive, HBase, ZooKeeper, Oozie, Spark, Sqoop, Flume, Pig, and Hue.
Strong understanding of Hadoop architecture, HDFS, distributed storage, and MapReduce concepts.
Strong analytical, problem-solving, debugging, and performance-tuning skills.
Excellent communication and collaboration skills.

Technologies

Hadoop
HDFS
MapReduce
Hive
Pig
Sqoop
HBase
ZooKeeper
Oozie
Apache Spark
Spark Streaming
Spark Structured Streaming
Scala
Flume
Flume NG
Kafka
Hue
HiveQL
Pig Latin
BigQuery
Cloudera
MapR
Hortonworks

Key competencies

Strong expertise in distributed data processing and big data architecture.
Deep understanding of batch, real-time, streaming, and event-driven data processing.
Strong hands-on programming skills in Scala and distributed data engineering frameworks.
Ability to design scalable, fault-tolerant, and high-performance data solutions.
Strong technical troubleshooting and root-cause analysis capabilities.
Ability to work independently while collaborating effectively with cross-functional teams.
Strong ownership, attention to detail, and commitment to data quality and operational excellence.

Desirable skills

End-to-end Hadoop administration and production support experience.
Hadoop infrastructure setup, software installation, configuration, upgrades, patching, monitoring, troubleshooting, and maintenance.
Experience administering Hadoop distributions such as Cloudera, MapR, Hortonworks.
Installing, configuring, and managing Hadoop ecosystem components such as Hive, Pig, HBase, ZooKeeper, Oozie, Spark, Sqoop, Flume, Hue.
Managing and monitoring HDFS, distributed file systems, and Hadoop clusters.
Managing, monitoring, scheduling, and troubleshooting MapReduce and distributed processing jobs.
Cluster capacity planning, resource management, health monitoring, and operational support.
Automating operational activities using scripting for backups, cluster monitoring, health checks, maintenance, and operational reporting.
Experience with version control, change management, release management, incident management, problem management, and root-cause analysis.

Compensation and location

Salary: $100,696.26 to $110,268.61 per year. Location: Irving, TX, onsite.

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