Data Scientist- Spark DataBricks Platform EoY Contract extension Jersey City, NJ This position is a back-end role that needs deep expertise in Apache Spark along with breadth of big data solution architecture experience. On a weekly basis, you will engage in product architecture, design and implementation activities while strategically aligning our technical roadmap for expanding the usage of the Databricks platform. Responsibilities Identify and drive new initiatives that enable customers to succeed in turning their data into value Build reference architectures, frameworks, solutions, how-to's, and prototypes Provide escalated level of support for critical product operational issues Architect, implement, andor validate migration of workloads from 3rd party databases and data platforms to Apache Spark. Build and tune AWS Glue ETL jobs for processing various file types into Parquet format, complete with job statistics reports. Evangelize Spark and Databricks across engineering department through lunch-box learnings and classeslabs. Qualifications Deep hands-on technical expertise with Apache Spark Minimum 5 years of design and implementation experience in Big Data technologies (Hadoop ecosystem, Kafka, NoSQL databases) Familiarity with data architecture patterns (data warehouse, data lake, streaming, LambdaKappa architecture) Outstanding verbal and written communication skills Comfortable with talking up and down the IT chain of command including directors, managers, architects and developers Passionate about learning new technologies and making customers successful Excellent presentation and whiteboarding skills Comfortable coding Python, Scala or Java IAM and infrastructureS3 security architecture experience in an enterprise setting. AWS RDS experience Aurora PostgreSQL, Aurora MySQL Familiarity with AWSEC2 cloud deployment models (Public vs. VPC) Preferred Qualifications BS MS in Computer Science or equivalent Proven track record within a data platform software vendor in a consultingservices function Experience working as or with Data Scientists Experienced with performance tuning, troubleshooting, and debugging Spark andor other big data solutions Familiarity with database and analytics technologies in the industry including Data WarehousingETL, Relational Databases, or MPP Associated topics: data analyst, data analytic, data integrity, data manager, data scientist, data warehouse, data warehousing, erp, mongo database administrator, teradata
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