Salary: 120,000 - 140,000 per annum + Benefits
Technology: AWS Jobs
Job Type: Permanent
Date Posted: 6/14/2019
Position: Big Data Engineer
About the Role
Our client has an exciting opportunity for someone with AWS data warehouse experience. This role gives you the best chance to work with the latest technology in big data and allows you to work on data pipelines, data lakes and data infrastructures.
The successful candidate will be highly experienced Big Data solution Architects to develop proposals and execute solution projects for top clients. You will have the ability to help design and build out AWS cloud platforms for their top clients, as well as creating analytic solutions to help solve existing business problems. The ideal candidate will have hands-on experience in a multitude of domains; including, but not limited to: experience and knowledge in Python, Spark, Scala, and R, extensive knowledge of AWS Pipelines and Database Use, AWS Architecting and Proof of Concept experience, experience with data processing tools in the AWS environment including Redshift, ETL and S3.
Responsibilities, Skills and Qualifications
* Building new, and scaling out existing ETL applications
* Candidate will assist in the development of a new process to speed up the load process and minimize existing process bottlenecks.
* Experience or working knowledge of AWS technologies such as S3 and EC2
*Collaborating with Data Scientists and designing various Data Science Models
* Coordinating data models with other engineering teams
* Developer will assist in the migration of an on premise system into Amazon Redshift.
* Designing and building out new data pipelines
* Database experience with functionalities that can be replicated in Redshift using plain SQL.
* Analyze, scrub, and integrate third-party data
* Candidate will review and analyze ETL process
* Experience with Aurora and Athena
* Develop and release using agile methodologies
* Significant data technology and analytics experience
* Must have experience with Spark concepts
* Hands on experience with AWS Big Data (Glue, Redshift, RDS, S3, and more)
* Experience analyzing requirements, designing and developing database solutions
* AWS Redshift experience
* Experience with SnapLogic
* Having worked with large volumes of Data.
* Competitive Base Salary
* Gym Membership
* Free Growth
* Free Lunch
* Vision Plans
* Paid Vacation
What's In It For You?
Work with us and you'll get the personalized experience you deserve - one you'll simply not find at any other recruitment agency. At Jefferson Frank, we find great people great jobs in AWS. I understand the need for discretion and would welcome the opportunity to speak to any Big Data and cloud analytics candidates that are considering a new career or job either now or in the future. Confidentiality is of the utmost importance. For more information on available AWS Big Data Jobs as well as the cloud market, I can be contacted at email@example.com or by calling 646-863-7442 (ext 7442). Please see www.jeffersonfrank.com for more information
Jefferson Frank is the Amazon Web Services (AWS) recruiter of choice. We work with organizations worldwide to find and deliver the best AWS professionals on the planet. Backed by private equity firm TPG Growth, we have a proven track record servicing the AWS permanent and contract recruitment market and, to date, have worked with over 30,000 organizations globally from our offices in North America, Europe, and Asia-Pacific. At Jefferson Frank, our mission is simple: we want happy customers. Whether you're an AWS professional walking into your dream AWS job, or an organization hiring an incredible contractor for your cloud migration project, our goal is to deliver an unrivalled customer experience.
Big Data / Data Science / Hadoop / Microsoft Business Intelligence / BI / Business Intelligence / SSRS / SSAS / SSIS / SQL / T-SQL / MDX / Azure / Cloud / AWS / Data Warehouse / ETL / Power BI / Architect / Big Data / Hadoop / Scala / Python / Apache / Hive / Spark / MS Azure / Amazon Web Services / AWS / EMR / RDS/ Redshift / S3 / EC2 / Lambda / Glue / Data Pipeline / Kafka / Power BI / Data Lake / Data Lake Analytics / Azure IoT Hubs / BLOB Storage / HDInsight / Data Factory / Machine Learning / SQL Data Warehouse / Steam Analytics / Ruby / DynamoDB / Kinesis