For the given job description <<The Senior Manager, Data Architecture & Data Engineering is responsible for translating business strategic goals into future-state data engineering and data science solutions. This includes delivery full life-cycle from execution roadmaps, to implementation, and to production operations. This role drives the creation and maintenance of enterprise data and analytics capabilities, data reference architectures, and integrated data & analytics technology roadmaps that will guide our strategic investments and enterprise strategy.Translate business strategic goals into actionable future-state data engineering and data science architectures and solutions.Delivery of full life-cycle Data Solutions from execution roadmaps, to implementation, and to operations. This includes a specific focus on ELT and ETL Data Pipeline solutions from inception to production.Lead end to end solution delivery of enterprise data warehouse, data marts, and data lake with governance.Drive the creation and maintenance of enterprise data and analytics capabilities, data solutions, and integrated data & analytics technology roadmaps that will guide our strategic investments and enterprise strategy.Deliver architecture connecting Data Science, Data Engineering, and Data Analytics practices together to deliver impactful data products.Strong partnership with DevOps, DataOps, business partners, engineering teams, and data management.A minimum of ten (10) years of experience in IT with a minimum (6) years in data architecture and data solutions are required.Successful track-record in managing a team of Data Engineers and Data ScientistsSkilled in hybrid cloud data platforms and analytical technologies including Azure andor GCP data infrastructure, Spark, Data Lake, Data Warehouse and Data Marts, BI reporting with PowerBI, Metadata Management, Data Governance, Master Data Management, Data Catalog, and Business Glossary.Ability to document, communicate, implement, and operationalize complex architectures.Experience with ELT and ETL Data Pipeline solutions from inception to production.Proficient in SQL, NoSQL and columnar databases.Experience with SparkPyspark and JSON.Excellent grasp of Computer Science fundamentals - data structures and algorithms.Must have Panda Data Frames knowledge and best practices, execution engines, DAGs (airflow, dagster, luigi, etc), and Kubernetes.Proficient with GitLabFamiliarity with Azure data factory preferred, Google data flow or AWS GlueExperience with Biomedical Informatics, S3Azure blob store, Machine Learning and AI, Unstructured Data, and Data Democratization is preferred.Experience with Agile methodologies, Kanban preferred, and using tools like Jira and Confluence to facilitate the work.Bachelor's degree in computer science or a related discipline required. Master's degree preferred. RECRUITERS NOTES: The role will definitely be hands-on and will require excellent communication skills. The hiring manager mentioned the following technologies: AImachine learning; data warehouses; product support; Cloud experienceAzure; must be open to new technologies. Working with the Product Development Team. Act as the point of contact; will create a group that helps the product teams. Create data warehouses for analytics. MUST have excellent communication skills  verbal and written. This person will envision strategy and must be able to effectively communicate that strategy to others.  The organization has asked me not to advertise the compensation. If you contact me I would be more than willing to share it with you. 
For over 50 years this non-profit organization has made it their mission to protect patients from unsafe and ineffective medical technologies and practices. More than 5,000 healthcare institutions and systems worldwide including four out of every five U.S. hospitals rely on the services of this organization to guide their operational and strategic decisions. In addition, they serve public and private payers, federal and state agencies, policymakers, ministries of health, associations, and accrediting agencies. Benefit from a healthy work-life balance while staying on the leading edge of technology and thriving in an innovative startup-like culture minus the risk. Sleep well knowing you are helping achieve a world where safe, high-quality healthcare is accessible to everyone. Excellent benefits to include work from home, flex-time and 19 days starting vacation.
Its a nice place to work!>> 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, No Fit

Fit assessment: No Fit