Additional Job Information:

Title : Big Data Engineer

Location : Atlanta, GA

Description:

Big Data Engineers are responsible for architecture, design and build of Big Data applications to support business strategies and deliver business value. A data engineer participates in all phases of the Data Engineering life cycle and will independently and collaboratively write project requirements, architect solutions, and perform data ingestion development and support duties. Building data ingestion pipelines is highly technical and requires advanced skills with computers and proficiency with Big Data tools and technologies such as SQL, Python/Scala, Spark, Spark Structured Streaming, Spark SQL, Kafka, Sqoop, Hive, Kudu, HBASE, Impala, S3, HDFS, or Cloud platforms such as AWS, Google Cloud Platform, Azure, etc. Data Engineers require ability to communicate effectively, both written and verbal, and have extensive experience working with business areas to translate their business data needs and data questions into project requirements.

Job Description

Client Corporation is currently seeking an experienced Data Engineer Big Data individual for their Midtown office in Atlanta, GA. The successful candidate must have Big Data engineering experience and must demonstrate an affinity for working with others to create successful solutions. Join a smart, highly skilled team with a passion for technology, where you will work on our state of the art Big Data Platforms. They must be a very good communicator, both written and verbal, and have some experience working with business areas to translate their business data needs and data questions into project requirements. The candidate will participate in all phases of the Data Engineering life cycle and will independently and collaboratively write project requirements, architect solutions and perform data ingestion development and support duties.

Skills and Experience:

Required :

6 years of overall IT experience

3 years of experience with high-velocity high-volume stream processing: Apache Kafka and Spark Streaming

• Experience with real-time data processing and streaming techniques using Spark structured streaming and Kafka
  • Deep knowledge of troubleshooting and tuning Spark applications

3 years of experience with data ingestion from Message Queues (Tibco, IBM, etc.) and different file formats across different platforms like JSON, XML, CSV

3 years of experience with Big Data tools/technologies like Hadoop, Spark, Spark SQL, Kafka, Sqoop, Hive, S3, HDFS, or

3 years of experience building, testing, and optimizing Big Data data ingestion pipelines, architectures, and data sets

2 years of experience with Python (and/or Scala) and PySpark/Scala-Spark

3 years of experience with Cloud platforms e.g. AWS, Google Cloud Platform, etc.

3 years of experience with database solutions like Kudu/Impala, or Delta Lake or Snowflake or BigQuery

2 years of experience with NoSQL databases, including HBASE and/or Cassandra

Experience in successfully building and deploying a new data platform on Azure/ AWS

Experience in Azure / AWS Serverless technologies, like, S3, Kinesis/MSK, lambda, and Glue

Strong knowledge of Messaging Platforms like Kafka, Amazon MSK & TIBCO EMS or IBM MQ Series

Experience with Databricks UI, Managing Databricks Notebooks, Delta Lake with Python, Delta Lake with Spark SQL, Delta Live Tables, Unity Catalog

Knowledge of Unix/Linux platform and shell scripting is a must

Strong analytical and problem-solving skills

Preferred (Not Required):

Strong SQL skills with ability to write intermediate complexity queries

Strong understanding of Relational & Dimensional modeling

Experience with GIT code versioning software

Experience with REST API and Web Services

Good business analyst and requirements gathering/writing skills

Qualification:
Bachelor s Degree required. Preferably in Information Systems, Computer Science, Electrical Engineering, Computer Information Systems or related field

For Big Data Engineer position:

1. Must have hands-on experience with Databricks
2. Must have hands-on experience with high-velocity high-volume stream processing: Apache Kafka and Spark Streaming a. Experience with real-time data processing and streaming techniques using Spark structured streaming and Kafka b. Deep knowledge of troubleshooting and tuning Spark applications
3. Must have hands-on experience with Python and/or Scala i.e. PySpark/Scala-Spark

4.Experience with Traditional ETL tools and Data Modeling

1. Strong knowledge of Messaging Platforms like Kafka, Amazon MSK & TIBCO EMS or IBM MQ Series
2. Experience with Databricks UI, Managing Databricks Notebooks, Delta Lake with Python, Delta Lake with Spark SQL, Delta Live Tables, Unity Catalog
3. Experience with data ingestion of different file formats across like JSON, XML, CSV
4. Knowledge of Unix/Linux platform and shell scripting
5. Experience with Cloud platforms e.g. AWS, Google Cloud Platform, etc. Experience with database solutions like Kudu/Impala, or Delta Lake or Snowflake or BigQuery

Best Regards,

Sethu Mathan, MBA

Senior Manager, IT Strategic Solution

Services You Can Trust

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7000 Peachtree Dunwoody Rd | Bldg. 11, Suite 301

Atlanta, GA 30328