For the given job description <<Title: Azure Data Engineer Location  Seattle, WA - In-Office Days: Monday, Tuesday, and ThursdayDuration  12 months Job Description:Independently design and develop programs and tools to support data pipelines including ingestion, curation, and provisioning of data for analytics, reporting and data science. Deliver key, complex business capabilities and platform features. Deliver high quality software using AgileScrum development methodologies. Identify and drive operational improvements for the team's data platform services.
ResponsibilitiesShould have experience with Azure Databricks, Spark, and Azure Data Factory Should have experience operationalizing production pipelines4 years of software development experience using Python  PySpark4 years of experience using software engineering fundamentals, including algorithm theory and data structures. 2 years of experience using CICD tools to build and deploy software systems.2 years of experience using relational and non-relational, NoSQL databases. 1 years of experience using Hadoop or Spark. 1 years of experience using data hygiene routines and models.Collaborate with development team, other Information Technology (IT) teams developer leads.Initiate process improvements for new and existing systems. Design, develop, implement, document, and test changes to an application subsystem.Code, test, debugs, documents, and implement complex software applications.Create more complex prototypes and ensure deliverables are high quality and meet user expectations.Support system and integration testing activities.Perform root cause analysis to identify permanent resolutions to software or business process issuesInitiate design reviews for new applications and adhere to software development standards. Coach, and mentor other team members.Perform cross-training and facilitate information sharing among team members.
>> the resume: <<Professional SummaryEnergetic Data Engineer in developing robust code for high-volume businesses. Strong decision-maker with 6 years of experience in Data engineering and help firms in designing and executing solutions for complex business problems involving large scale data warehousing, real-time analytics and reporting solutions. Ability to translate business questions and concerns into specific quantitative questions that can be answered with available data using sound methodologies.
SkillsPython 3.x, R, SQLHadoop, Apache SparkHive, Pig, Kafka, Sqoop, OozieTeradata, SnowflakeAmazon S3,EMR,LambdaGit, Jenkins, SplunkMS OfficeMicrosoft Visual C#.NET
Work HistoryData Engineer,04/2020toCurrentAvanade–Bangor,ME,Combining data from multiple source systems (Profile, Systematics, etc..) and multiple platforms (Snowflake, OneLake, Hubs) and computing canonical gold-star metrics “once and for all” to cut operational costs.Develop Spark jobs to transform data and apply business transformation rules to load/process data across enterprise and application specific layers.Experience in building/operating/maintaining fault tolerant and scalable data processing integrations using AWS.Configured S3 buckets with various life cycle policies to archive the infrequently accessed data based on requirement.Good working experience on submitting the Spark jobs which shows the metrics of the data which is used for Data Quality Checking.Working on building efficient data pipelines that transform high volume data into a format used for analytical, fraud prevention and ML use cases.Extensively used Splunk Search Processing Language (SPL) queries, Reports, Alerts and Dashboards.Excellent knowledge of source control management concepts such as Branching, Merging, Labeling/Tagging and Integration, with tool like Git.Performing Data Quality checks like row count, schema validation, Hash key validation for all data movement between applications.Data Engineer,08/2019to04/2020Avanade–Burlington,NC,Responsible for designing and developing various analytical solutions for gaining analytical insights into large data sets by ingesting and transforming these datasets in the Big Data environment using technologies like Spark, Sqoop, Oozie, HIVE.Scheduling jobs to automate the process for regular executing jobs worked on using Oozie.Developed Oozie workflow schedulers to run multiple Hive and Pig jobs that run independently with time and data availability.Familiar with data architecture including data ingestion pipeline design, Hadoop information architecture, data modeling and data mining,machine learning and advanced data processing.All the projects which I have worked for are Open Source Projects and has been tracked using JIRA.Parallel copying of files between various clusters using Distcp, Kafka in Hadoop.Data Scientist Intern,09/2018to12/2018Ascend Learning–Memphis,TN,Acquire, clean, integrate, analyze and interpret disparate datasets using a variety of statistical data analysis and data visualization methodologies, reporting and authoring findings where appropriate.Developed Linear Mixed Effects Models for Boston Ed-fi dataset to estimate the teacher contribution to the student test scores.Random intercept model which utilized a pre-post-test design and included fixed effects for student demographics and a growth model where students were nested by time (random slope and intercept) and teacher was tested.Generated various Clustering models for entire West Virginia department of education and evaluated cluster’s performance.Big Data Engineer,01/2014to07/2017Verizon–,,Identify customer's digital analytical needs and engage with customer and principal architects daily, understand the business requirements for big data analytical solutions and break down large scale requirements into detailed system specifications.Moving data to HDFS framework using SQOOP from Teradata, SQL Server.Good working experience on Hadoop tools related to Data warehousing like Hive, Pig and also involved in extracting the data from these tools on to the cluster using Sqoop.Solved performance issues in Hive with understanding of joins, groups, bucketing, partitions and working on them using HiveQL.Deployed programs written in PySpark to run Spark MLlib, for analytics and reduced customers churn rate by 25%.
EducationMaster of Science:Business Analytics,Expected in4 2020toThe University Of Texas At Dallas-Richardson,TXGPA:
SkillsPython 3.x, R, SQLHadoop, Apache SparkHive, Pig, Kafka, Sqoop, OozieTeradata, SnowflakeAmazon S3,EMR,LambdaGit, Jenkins, SplunkMS OfficeMicrosoft Visual C#.NET>>. The result is, Potential Fit

Fit assessment: Potential Fit