At Perficient youll deliver mission-critical technology and business solutions to Fortune 500 companies and some of the most recognized brands on the planet. And youll do it with cutting-edge technologies, thanks to our close partnerships with the worlds biggest vendors. Our network of offices across North America, as well as locations in India and China, will give you the opportunity to spread your wings, too.
Were proud to be publicly recognized as a Top Workplace year after year. This is due, in no small part, to our entrepreneurial attitude and collaborative spirit that sets us apart and keeps our colleagues impassioned, driven, and fulfilled.
Perficient currently has a career opportunity for a MapR Spark Developer
Job Overview
One of our large clients has made strategic decision to move all order management and sales data from their existing EDW into MapR platform. The focus is fast ingestion and streaming analytics. This is a multiyear roadmap with many components that will piece into a larger Data Management Platform. Perficient subject matter expert will work with the client team to move this data into new environment in a fashion that will meet requirements for applications and analytics.
As a Data developer, you will be incharge of developing data pipelines using Spark and other ingestion framework.
Responsibilities
Prov- ide end to end vision and hands on experience with MapR Platform especially best practices around HIVE and HBASE Shoul
- d be a Rockstar in HBase and Hive Best PracticesAbili
- ty to focus on ingestion and transformationUnder
- stand MDM and think about MDM in HDFSAbili
- ty to design solutions for different use cases
- Worked with different data formats (Parquet, Avro, JSON, XML, etc.)
- Troubleshoot and develop on Hadoop technologies including HDFS, Kafka, Hive, Pig, Flume, HBase, Spark, Impala and Hadoop ETL development via tools such as ODI for Big Data and APIs to extract data from source.
- Translate, load and present disparate data-sets in multiple formats and from multiple sources including JSON, Avro, text files, Kafka queues, and log data.
- Lead workshops with many teams to define data ingestion, validation, transformation, data engineering, and Data MOdeling
- Performance tune HIVE and HBASE jobs with a focus on ingestion
- Design and develop open source platform components using Spark, Sqoop, Java, Oozie, Kafka, Python, and other components
- Lead the technical planning & requirements gathering phases including estimate, develop, test, manage projects, architect and deliver complex projects
- Participate and lead in design sessions, demos and prototype sessions, testing and training workshops with business users and other IT associates
- Contribute to the thought capital through the creation of executive presentations, architecture documents and articulate them to executives through presentations
Qualifications
- At least 3+ years of experience on working with large projects including the most recent project in the MapR platform
- At least 5+ years of Hands-on administration, configuration management, monitoring, performance tuning of Hadoop/Distributed platforms
- Should have experience designing service management, orchestration, monitoring and management requirements of cloud platform.
- Hands-on experience with Hadoop, Teradata (or other MPP RDBMS), MapReduce, Hive, Sqoop, Splunk, STORM, SPARK, Kafka and HBASE (At least 2 years)
- Experience with end-to-end solution architecture for data capabilities including:
- Experience with ELT/ETL development, patterns and tooling (Informatica, Talend)
- Ability to produce high quality work products under pressure and within deadlines with specific references
- VERY strong communication, solutioning, and client facing skills especially non-technical business users
- At least 5+ years of working with large multi-vendor environment with multiple teams and people as a part of the project
- At least 5+ years of working with a complex Big Data environment
- 5+ years of experience with Team Foundation Server/JIRA/GitHub and other code management toolset
Preferred Skills And Education
Masters degree in Computer Science or related field
Certification in Azure platform
Perficient full-time employees receive complete and competitive benefits. We offer a collaborative work environment, competitive compensation, generous work/life opportunities and an outstanding benefits package that includes paid time off plus holidays. In addition, all colleagues are eligible for a number of rewards and recognition programs including billable bonus opportunities. Encouraging a healthy work/life balance and providing our colleagues great benefits are just part of what makes Perficient a great place to work.
More About Perficient
Perficient is the leading digital transformation consulting firm serving Global 2000 and enterprise customers throughout North America. With unparalleled information technology, management consulting and creative capabilities, Perficient and its Perficient Digital agency deliver vision, execution and value with outstanding digital experience, business optimization and industry solutions.
Our work enables clients to improve productivity and competitiveness; grow and strengthen relationships with customers, suppliers and partners; and reduce costs. Perficient's professionals serve clients from a network of offices across North America and offshore locations in India and China. Traded on the Nasdaq Global Select Market, Perficient is a member of the Russell 2000 index and the S&P SmallCap 600 index.
Perficient is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national, origin, disability status, protected veteran status, or any other characteristic protected by law.
Disclaimer: The above statements are not intended to be a complete statement of job content, rather to act as a guide to the essential functions performed by the employee assigned to this classification. Management retains the discretion to add or change the duties of the position at any time.
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