Data Engineer (SQL, DB, SAS) | Hybrid - Bentonville, ARPosition Type: ContractLocation: Bentonville, ARJob DescriptionRequires knowledge of analytics/big data analytics/automation techniques and methodsBusiness understandingPrecedence and use casesBusiness requirements and insightsTo translate/co-own business problems within one's discipline to data related or mathematical solutionsIdentify appropriate methods/tools to be leveraged to provide a solution for the problemShare use cases and gives examples to demonstrate how the method would solve the business problemRequires knowledge of understanding of business value and relevance of data and data enabled insights/decisionsAppropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability, etc.Understanding of the methods and applications that unlock the monetary value of data assetsTo understand, articulate, interpret, and apply the principles of the defined strategy to unique, moderately complex business problems that may span one or main functions or domainsRequires knowledge of data quality management techniques and standardsBusiness metadata definitions and content data definitionsData profiling tools, data cleansing tools, data integration tools, and issues and event management toolsUnderstanding of user's data consumption, data needs, and business implicationsData modeling, storage, integration, and warehousingData quality framework and metrics User access best practicesEnterprise data architecture, modeling and design, storage, integration, and warehousingEnterprise data quality framework and metrics Enterprise data strategyEnterprise data quality strategyEnterprise strategy to address regulatory and ethical requirements and policies around data privacy, security, storage, retention, and documentation.To promote and educate others on data quality awarenessProfile, analyze, and assess data qualityTest and validate data quality requirementsContinuously measure and monitor data qualityDeliver against data quality service level agreementsManage operational Data Quality Management proceduresManage data quality issues and leads data cleansing activities to remove data quality defects, improve data quality, and eliminate unused dataDetermine user accessibility and removes or restricts user access as neededInterpret company and regulatory policies on dataEducate others on data governance processes, practices, policies, and guidelinesRequires knowledge of relevant Knowledge Discovery in Data (KDD) tools, applications, or scripting languages such as SQL, Oracle, Apache Mahout, MS Excel, Python Statistical techniques (for example, mean, mode, median, variance, standard deviation, correlation, and sorting and grouping)Research analysis standards and activitiesDocumentation procedures such as drafting, editing, Bibliography formatRelevant Knowledge Discovery in Data (KDD) tools, applications, or scripting languages such as SQL, DB, SAS, Oracle, Apache Mahout, MS Excel, PythonKDD industry best practices and emerging trends.To collect and tabulate data and evaluate results to determine accuracy, validity, and applicability.Support the identification and application of statistical techniques based on requirements.Apply suitable technique under direction from leadership.Assist in the planning, design and implementation of an exploratory data analysis research projects.Understand existing statistical models and identify and recommend statistical models based on hypothesis.Use advanced Knowledge in Data Discovery tools to write queries and analyze data to identify patterns, trends, outliers, and correlations.Conduct statistical analysis (for example hypothesis tests, confidence intervals) and build basic statistical models using relevant packages/software suites.Designs, develops, and implements Hadoop eco-system based applications to support business requirements.Follows approved life cycle methodologies, creates design documents, and performs program coding and testing.Resolves technical issues through debugging, research, and investigation.Experience/Skills Required:Bachelor's degree in Computer Science, Information Technology, or related field and 5 years' experience in computer programming, software development or related3+ years of solid Java and 2+ years' experience in design, implementation, and support of solutions big data solution in Hadoop using Hive, Spark, Drill, Impala, HBaseHands on experience with UNIX, Teradata and other relational databases.
Experience with @Scale a plus.Strong communication and problem-solving skills