Kforce's client, one of the world's largest financial institutions, is hiring an 6-person scrum team of AWS-EMR PySpark Hadoop Developers in Wilmington (DE), Plano (TX) & New York City (NY). This is an opportunity for quick fulltime employment with Client. Please note Lead, VP Titled, Hands-on Developer will need to be located in Plano, TX (Dallas) and will mentor a team of mobile application and full-stack developers, fostering collaboration and growth.
Responsibilities:
Design and implement scalable and efficient data pipelines using AWS and Data Lakehouse Platform services
Leverage AWS cloud services like S3, Kinesis, Redshift, EMR, Glue, Lambda, and others in combination with Data Lakehouse platform/Apache Spark Integration for advanced data processing and analytics
Develop and maintain data lakes and data warehouses on AWS and Data Lakehouse Platform, ensuring data integrity and accessibility
Optimize data storage and processing for performance and cost efficiency.
Automate data workflows and ensure high data quality and reliability
Monitor, troubleshoot, and resolve data pipeline issues
Organizing and managing data within the environment, ensuring it is stored efficiently, securely, and in a manner that supports easy access and analysis
Monitor the performance of data processes and queries and optimize efficiency and speed
Ensure high standards of data quality and implement data governance practices
Provide ongoing support for the platform, troubleshoot any issues that arise, and ensure high availability and reliability of data infrastructure
Create documentation for the platform infrastructure and processes, and train other team members or users on the platform effectively
Setup configure, implement, and maintain the data lake and respective tools
REQUIREMENTS:
BS in Computer Science, IT, Software or Computer Engineering, Data Science or Analytics, Mathematics or related field
AWS certification
5 years of experience in big data analytics, data engineering, or related roles
Experience in designing, building, and maintaining data warehouses. Understanding of data modeling, data warehousing, and data lake concepts
Proficiency in programming languages such as Python, Java, Scala, and scripting languages like Bash or PowerShell
Experience with big data technologies, such as Apache Hadoop, Spark, Kafka, and others
Hands-on experience with AWS services such as S3, Glue, Redshift, EMR, Athena, etc.
Proficiency in SQL and experience with relational databases
Experience in building and optimizing big data pipelines, architectures, and data sets
Familiarity with ETL tools, processes, and data integration techniques
Excellent communication and team collaboration skills
Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless
and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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