For the given job description <<Title: Sr. Data EngineerLocation: Austin, TxDuration: 6 MonthsPay Rate: $65HR - $70HR on W2
Requirements:Bachelors degree in Computer Science or related field plus 4+ years of relevant work experience or a Master's degree plus 2+ years of relevant work experience or a PhD plus 0-1 years of relevant experienceIn lieu of a degree, qualified candidates would require 8+ years of relevant professional experienceExcellent with SQLExcellent programming skills in Python and ideally demonstrating an aptitude via experience with multiple languagesExcellent understanding of patterns for data ingest into data warehouse, ingest, cleansing, standardizing, etc., in addition to different data structures like normalized, denormalized, starExcellent experience supporting Snowflake Data Warehouse, including Snowpipe (including streams), tasks, transformations, views, dynamic tables. This should include advanced skills in ensuring efficient utilization of Snowflake compute and the ability to optimize workloads and warehouseBroad experience with Cloud PaaS capabilities, ideally AWS CloudWatch, Lambda, Step Functions, SNSSQS, DynamoDB, etc.Experience utilizing reporting and data insights toolsExperience in supporting analytics teams data needs, in addition to customer and business reporting.
What you'll be doing:Provides Data Engineering support for areas such as Finance, Sales, Business Intelligence, Product Development andor other business usersWorks with data consumers and Project Managers to determine logical and physical database designs for analytics modelsCreates and maintains optimal data pipeline architecturesEnsures architectures are aligned with and support business requirements;Ensures that required data is available, can be trusted and is readily accessible by those who need itInfluences the data infrastructure roadmapIdentifies, designs and implements internal data management process improvementsPlays a key role in application development projects to evolve the companys database architecture and designWorks with internal and external data providers on data validation, providing feedback and making customized changes to data feeds and data mappings for analytical and operational useAutomates manual processes, transforming them into repeatable capabilitiesWorks with fellow team members to ensure design, development and execution align with and support adjacencies and adhere to established architectural standards.
Top 5 Must Haves:Excellent with SQLExcellent programming skills in Python and ideally demonstrating an aptitude via experience with multiple languagesExcellent understanding of patterns for data ingest into data warehouse, ingest, cleansing, standardizing, etc., in addition to different data structures like normalized, denormalized, star;Excellent experience supporting Snowflake Data Warehouse, including Snowpipe (including streams), tasks, transformations, views, dynamic tables. This should include advanced skills in ensuring efficient utilization of Snowflake compute and the ability to optimize workloads and warehouseBroad experience with Cloud PaaS capabilities, ideally AWS CloudWatch, Lambda, Step Functions, SNSSQS, DynamoDB, etc.
Thank you!>> 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, 

Fit assessment: Good Fit