Job Description :
Job Title: Data Engineer - Hadoop/Spark

Location: Boynton Beach,FL & Bradenton, FL

Duration: 6 months


BigData and Hadoop Ecosystems,

Microsoft Azure,


Apache & Spark,



Essential Skills:

The Data Engineer will be responsible for building, maintaining data pipelines and data products to ingest, process large volume of structured / unstructured data from various sources.

The Data engineer will work on analyzing the data needs, migrating the data into an Enterprise data lake, build data
products and reports.

The role requires experience with building real time and batch based ETL pipelines with strong understanding of big
data technologies and distributed processing frameworks with.

Skill Need so Expertise working with large scale distributed systems (Hadoop, Spark

Strong understanding of the big data cluster, and its architectureo Experience building and optimizing big data ETL
pipelines.o Advanced programming skills with Python, Java, Scala

Good knowledge of spark internals and performance tuning of spark jobs.

Strong SQL skills and is comfortable operating with relational data models and structure.

Capable of accessing data via a variety of API/RESTful services.

Experience with messaging systems like Kafka.

Experience with No SQL databases. Neo4j, mongo, etc.

Expertise with Continuous Integration/Continuous Delivery workflows and supporting applications.

Exposure to cloud environments and architectures. (preferably Azure)o Ability to work collaboratively with other

Experience with containerization using tools such as Docker.

Strong knowledge of Linux and Bash. Can interact with the OS at the command line and create shell scripts to
automate workflows.

Advanced understanding of software development and collaboration, including experience with tools such as Git.

Excellent written and verbal communication skills, comfortable presenting in front of non-technical audiences.
Essential Responsibilities include but not limited to

Design and develop ETL workflows to migrate data from varied data sources including SQL Server, Netezza, Kafka
etc. in batch and real-time.

Develop checks and balances to ensure integrity of the ingested data.

Design and Develop Spark jobs as per requirements for data processing needs.

Work with Analysts and Data Scientists to assist them in building scalable data products.

Designs systems, alerts, and dashboards to monitor data products in production