• Us Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 8th Jan 2021

Title: Data Engineer

Location: Detroit, MI - 100% Remote

Duration: 6+ months

Candidate should have 10 Years of exp at least 

Top three Skills:

1) PySpark - Python in Spark - creating data pipelines

2) AWS Serverless Analytics Tools - Glue, EMR, Redshift, S3, Lakeformation

3) Big Data fundamentals - core understanding of building data pipelines, data modeling, Linux

Job description:

The Data Engineer is responsible for engaging in the design, development and maintenance of the big data platform and solutions at Rock Central. This includes the platform host data sets that support various business operations and enable data-driven decisions as well as the analytical solutions that provide visibility and decision support using big data technologies. The Data Engineer is responsible for administering a Hadoop cluster, developing data integration solutions, resolving technical issues, and working with Data Scientists, Business Analysts, System Administrators and Data Architects to ensure the platform meets business demands. This team member also ensures that solutions are scalable, include necessary monitoring, and adhere to best practices and guidelines. The Data Engineer helps mentor new team members and continues to grow their knowledge of new technologies.

Responsibilities:

• Develop ELT processes from various data repositories and APIs across the enterprise, ensuring data quality and process efficiency
• Develop data processing scripts using Spark
• Develop relational and NoSQL data models to help conform data to meet users’ needs using Hive and HBase
• Integrate platform into the existing enterprise data warehouse and various operational systems
• Develop administration processes to monitor cluster performance, resource usage, backup and mirroring to ensure a highly available platform
• Address performance and scalability issues in a large-scale data lake environment
• Provide big data platform support and issue resolutions to Data Scientists and fellow engineers

Requirements:

• Master's degree in computer science, software engineering or a closely related field
• 2 years of experience with Hadoop distribution and ecosystem tools such as Hive, Spark, NiFi and Oozie
• 2 years of experience developing batch and streaming ETL processes
• 2 years of experience with relational and NoSQL databases, including modeling and writing complex queries
• 1 Year of experience with AWS Serverless Analytic tools - Glue, EMR, Redshift, S3, Lakeformation
• Proficiency in at least one programming language, such as Python or Java
• Experience with Linux system administration, scripting and basic network skills
• Excellent communication, analytical and problem-solving skills 

Additional Information:

Subvendor/H1 candidates are fine. Quicken Loans is fine with 100% remote candidates for this engagement.

Work Environment:

Strong Scaled Agile environment, will work on part of Scrum teams within Data Intelligence group. Roughly 380 people in Data Intelligence on over 30 teams. Each Scrum team has 8-15 depending on it's focus. 
 

Who is the Internal/External Customer:

External data consumer's a Rock Connections 

Impact to the Internal/External Customer:

Rock Connections will have a brand new data environment built completely on AWS. 

Business Challenge:

Rock Central is building out a new data infrastructure for a sister company within the Rocket Companies Family - Rock Connections. They are building them a solution from scratch on AWS. This is due to a split of the Rock Connections environment between Rock Connections and Rocket Auto. 

EVP:

Rock Central is a professional services organization that supports the other 90 companies that make up the Rocket Companies Family. Rocket Companies recently had their IPO and the family of companies have consistently been rewarded as a best place to work. 

Non-Technical Skills

Experience working with Lead and/or Call Center Analytics data is a plus

Please run these questions past all candidates and send to me with sub package - 1) What/when is the last code you pushed into production? What language was it written in? What was it for? Bonus question: What is the version control tool used and what tool was used to deploy the code?