Job Description:

Job Description:

Designs and develops Data and Analytics solutionsPerforms data analysis, data architecture, data engineering activitiesDesigns and builds data ingestion pipelines; develops data transformation, cleansing and preparation processesDesigns and builds data storage solutions including database objects and data structuresTakes ownership of complex data-level or database incidents and problems and provides resolutions in a timely mannerProvides advisory and consultation services to determine the right solutionUtilizes best practices, work plans, checklists and defined processesProactively supports application teamsPerforms optimizationParticipates in project technical reviewsLeads or participates in work product reviewsEngages SMEs or vendors to provide assistance to resolve more complex issues as required

Technology and Functional Skills:

Data Integration, Extract-Transform-Load (ETL), Data Ingestion, Data Cleansing, Data Preparation, DatabaseData Warehouse, Data Lake, and Business Intelligence (BI) conceptsLanguage and Toolset: SQL, Python, PySpark, ELK (Elasticsearch, Logstash, Kibana)ETL Tool : Informatica, Talend, DataStage, SAP BODS, etc.Preferred - experience in Oracle Cloud Infrastructure(A plus) Azure data platform and components: Azure Data Factory, Databricks, Blob Storage, Synapse, SQL DB/DW, Event Hubs, etc.(A plus) AWS data platform and components: S3, Redshift, Spectrum, Athena, Aurora, CLI, etc.(A plus) GCP data platform and components: BigQuery, Dataflow, Dataprep, Pub/Sub, etc.(A plus) Big Data: Hadoop, Hadoop ecosystem, Spark, Scala, etc.

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