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.
Qualifications
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.
