BigData Engineer / Architect

Responsibilities and Duties

• Participate in technical planning & requirements gathering phases including architectural design, coding, testing, troubleshooting, and documenting big data-oriented software applications.
• Responsible for the ingestion, maintenance, improvement, cleaning, and manipulation of data in the business’s operational and analytics databases, and troubleshoots any existent issues.
• Implementation, troubleshooting, and optimization distributed solutions based on modern big data technologies like Hive, Hadoop, Spark, Elastic Search, Storm, Kafka, etc. in both an on premise and cloud deployment model to solve large scale processing problems
• Design, enhance and implement ETL/data ingestion platform on the cloud.
• Strong Data Warehousing skills, including: Data clean-up, ETL, ELT and handling scalability issues for enterprise level data warehouse
• Capable of investigating, familiarizing and mastering new data sets quickly
• Strong troubleshooting and problem-solving skills in large data environment
• Experience with building data platform on cloud (AWS or Azure)
• Experience in using Python, Java or any other language to solving data problems
• Experience in implementing SDLC best practices and Agile methods.

Required Skills:

• Data architecture/ Big Data/ ETL environment
• Experience with ETL design using tools Informatica, Talend, Oracle Data Integrator (ODI), Dell Boomi or equivalent
• Big Data & Analytics solutions Hadoop, Pig, Hive, Spark, Spark SQL Storm, AWS (EMR, Redshift, S3, etc.)/Azure (HDInsight, Data Lake Design)
• Building and managing hosted big data architecture, toolkit familiarity in: Hadoop with Oozy, Sqoop, Pig, Hive, HBase, Avro, Parquet, Spark, NiFi
• Foundational data management concepts - RDM and MDM
• Experience in working with JIRA/Git/Bitbucket/JUNIT and other code management toolsets
• Strong hands-on knowledge of/using solutioning languages like: Java, Scala, Python - any one is fine
• Healthcare Domain knowledge

Required Experience, Skills and Qualifications

Qualifications:

• Bachelor’s Degree with a minimum of 6 to 9 + year’s relevant experience or equivalent.
• Extensive experience in data architecture/Big Data/ ETL environment.

All your information will be kept confidential according to EEO guidelines.

gathering phases including architectural design, coding, testing, troubleshooting, and documenting big data-oriented software applications.

Responsible for the ingestion, maintenance, improvement, cleaning, and manipulation of data in the business’s operational and analytics databases, and troubleshoots any existent issues.

Implementation, troubleshooting, and optimization distributed solutions based on modern big data technologies like Hive, Hadoop, Spark, Elastic Search, Storm, Kafka, etc. in both an on premise and cloud deployment model to solve large scale processing problems

Design, enhance and implement ETL/data ingestion platform on the cloud.

Strong Data Warehousing skills, including: Data clean-up, ETL, ELT and handling scalability issues for enterprise level data warehouse

Capable of investigating, familiarizing and mastering new data sets quickly

Strong troubleshooting and problem-solving skills in large data environment

Experience with building data platform on cloud (AWS or Azure)

Experience in using Python, Java or any other language to solving data problems

Experience in implementing SDLC best practices and Agile methods.

Required Skills:

• Data architecture/ Big Data/ ETL environment
• Experience with ETL design using tools Informatica, Talend, Oracle Data Integrator (ODI), Dell Boomi or equivalent
• Big Data & Analytics solutions Hadoop, Pig, Hive, Spark, Spark SQL Storm, AWS (EMR, Redshift, S3, etc.)/Azure (HDInsight, Data Lake Design)
• Building and managing hosted big data architecture, toolkit familiarity in: Hadoop with Oozy, Sqoop, Pig, Hive, HBase, Avro, Parquet, Spark, NiFi
• Foundational data management concepts - RDM and MDM
• Experience in working with JIRA/Git/Bitbucket/JUNIT and other code management toolsets
• Strong hands-on knowledge of/using solutioning languages like: Java, Scala, Python - any