Data Engineer Resume. Data lakes store data of any type in its raw form, much as a real lake provides a habitat where all types of creatures can live together.A data lake is an Home. The data lake should hold all the raw data in its unprocessed form and data should never be deleted. A link to a personal Github or other page to show off data science work you’ve done. ), Basic knowledge of machine learning, statistics, optimization or related field is a plus, Facilitating cross-functional requirement gathering meetings, Developing relationships with internal Customers and Service Providers, Architect and evolve Rogers Enterprise Big Data Platform to support Enterprise data management, operational, reporting and analytical systems and applications, Design, install, configure and administer Rogers Enterprise Big Data Hadoop platform: Dev, QA, Production clusters, applications and services in both physical and virtualized environments, Implement best practices to design, install and administer services to secure Big Data environments, applications and users including Kerberos, Knox and Ranger, Implement best practices to configure and tune Big Data environments, application and services, including capacity scheduling, Install and configure high performance distributed analytical applications utilizing Enterprise Big Data platform, including commercial (SAS) and open source Machine Learning frameworks, Work closely with hardware & software vendors, design & implement optimal solutions, Conduct day-to-day administration and maintenance work on the Big Data environment, Look after both incident & change management, Manage capacity utilization to ensure high availability and multi-tenancy of Big Data systems, Perform capacity planning based on Enterprise project pipeline and Enterprise Big Data roadmap, Provide technical inputs during project solution design, development, deployment and maintenance phases, Help with purchase decisions based on business requirements, Assist with preparing and reviewing vendor SOWs, Assist and advise network architecture and datacenter teams during hardware installations, configuration and troubleshooting, Actively participate in architecture and design of the next generation Rogers Big Data platforms, A degree in Computer Science, Engineering, Systems Administration, Technology or a related field, 2+ years of Production Big Data Administration experience, Hortonworks HDP 2.0 / YARN production Administration experience, Minimum 1 year of production experience with Hadoop installation, performance tuning, configuration, optimization, job processing, In-depth understanding of best practices and production experience with Hadoop cluster security frameworks (authentication and authorization): Kerberos, Knox, Ranger, Production experience with Hadoop components and services: Hive, Pig, Hbase, Sqoop, Falcon, Oozie, Ambari, Experience with Flume/Kafka/Storm is a strong asset, Experience administering both virtualized and physical environments, Strong virtualization skills and production experience with VMWare VSphere 5.1 / 5.5 is an asset, Expert Linux / Unix administration skills and experience, Strong Systems Networking administration skills and experience, Experience within the Telecommunication industry is an asset, Highly motivated and very proactive individual, dedicated to follow-up/follow through without reliance on management for direction, Ability to gather and understand information discovery, business intelligence reporting, query, analytic, and real-time data processing requirements (including the underlying business requirements that drive selection of the tools) and effectively recommend solutions, Ability to gather data management system requirements, position how and why Hadoop clusters, NoSQL databases, and data warehouses are deployed, and effectively recommend solutions, Ability to gather data integration and data ingestion requirements from a variety of structured, semi-structured, and streaming data sources and effectively recommend solutions, Ability to discuss tradeoffs in on-premise and cloud-based approaches, understand data transmission requirements, and suggest viable approaches, Ability to apply information / enterprise architecture methodologies and best practices (such as TOGAF and Oracle’s OADP) during discovery and recommendations and prepare appropriate deliverable, Ability to communicate with lines of business and technical audiences, Ability to apply knowledge of certain industries and uncover the drivers of potential projects, Ability to apply expertise in Oracle products and strategies (and / or those of competitors) that provide needed solutions, Ability to work with other team members and drive initiatives and initial project planning including architecture, value determination, targeted demonstrations, and proof of value testing with well defined success criteria, Any knowledge of some or all of the following products would be considered beneficial: Oracle Advanced Analytics, Big Data Appliance, Oracle Big Data Connectors, Oracle Big Data SQL, Cloudera Hadoop, Oracle NoSQL Database, Oracle Big Data Discovery, Oracle Data Integrator, Oracle Event Processing and Big Data cloud services solutions, Ability to both understand and anticipate requirements to make the global DIL offer evolve, Identify key technical bricks to evaluate and implement in the platforms, Assists entities architects to design integration architecture to work with datas & digital assets, Articulate pros and cons of various technologies and platforms, Document use cases, solutions and recommendations, Help program and project managers in the design, planning and governance of implementing projects of any king, Perform detailed analysis of business problemes and technical environments and use this in designing the solution, Experience with a wide range of big data architectures Hadoop and non Hadoop including HDFS, Redis, Pig, Hive, Impala, Mahout, Spark, Shark, R, Tableau and other big data frameworks. Some companies, states, and countries have non-discrimination policies about what kind of information can be included on your resume. Resume Examples. Course projects that involved data science work - if you’ve gone through the effort of learning data science, you sure have practiced your skills on quite a few practical exercises. Then go through our 10 Career Change Resume Tips (with examples) and see what you’re missing out. They differ in terms of data, processing, storage, agility, security and users. Over 9 years of diverse experience in Information Technology field, includes Development, and Implementation of various applications in big data and Mainframe environments. This data lands in a data lake for long term persisted storage, in Azure Blob Storage or Azure Data Lake Storage. Serverless Data Lake Workshop. Focus on impact rather than responsibilities - data mining, statistical analysis, and data visualization will be on pretty much any data scientists’ resume. Over 8 years of IT experience in Database Design, Development, Implementation and Support using various Databasetechnologies(SQL Server 2008/2012, 2016 T - SQL, Azure Big Data) in both OLTP, OLAP and data warehousing environmentsExpertise in SQL Server and T-SQL (DDL, DML and DCL) in constructing Tables, Joins, Indexedviews, Indexes, Complex Storedprocedures, Triggers, and useful … We analyzed over 100,000 resumes and job offers on to discover what skills were most in demand for data scientists. These are some examples of job descriptions we have handpicked from real Data Architect resumes for your reference. ", "Your resume should show employers what you’ve done outside of your and Enhancv helped me accomplish that. Big Data Engineer Sample Resume Name : XXXX Big Data Engineer – TD Bank. Still, you should use this as a general suggestion, not a rule set in stone. You can store your data as-is, without having to first structure the data, and run different types of analytics—from dashboards and visualizations to big data processing, real-time analytics, and machine learning to guide better decisions. Informatica MDM is the technology used for managing the master data … Still, consider these two examples - one has everything a recruiter would be looking for, the other has a lot left out. If you're ready to apply for your next role, upload your resume to Indeed Resume to get started. A data lake is a vast pool of raw data, the purpose for which is not yet defined. ", "At Tesla, the competition is very high, but Enhancv put me in front of other applicants!". Skills For Senor MS Azure Solutions Architect Resume Data Architect. SUMMARY. - 2+ years, BRMS/Drools - knowledge and/or experience is preferred, TOGAF/DMBOK - knowledge and/or experience with standards is preferred, Data Analysis - 3+ years (technical data analysis), SAP PowerDesigner, SAP Information Steward preferred, Experience using tools such as RedGate, Atlassian (Jira), Wiki, Visual Studio, TFS, PragmaticWorks, Power Designer, Tortoise/SVN, Git, SQL Server, Lamda Architecture including Machine Learning knowledge, AWS Codebase Migrations for large scale BI/DWH projects, 10+ years experience in information technology and/or IT professional services, 6+ years in client facing roles with data architecture and providing project management and oversight within professional services, 3+ years of hands-on big data technology experience, Certification with one of the Hadoop distribution - Cloudera, MapR, Hotonworks, Prior experience with Big Data ETL tools like Informatica BDM, Talend, Prior experience with Spark ingestion/ compute, Hands on experience with few of the tools like pig, flume, sqoop, oozie, Kafka, Nifi, minifi, Impala, Scala, etc, Prior experience with R, Python is a plus, Experience with NoSQL database like Cassandra, MongoDB, NuoDB, Couchbase, HBase, Redis is a plus, Experience with various technology platforms, application architecture, design, and delivery including experience architecting large big data enterprise data lake projects, Strong writing and client facing communications with the ability to effectively develop and maintain client relationships, Excellent analytical and problem solving abilities, Action oriented and able to prioritize while handling multiple tasks, Hands on experience with designing and implementing distributed architecture systems to terabyte/petabyte using OpenSource Software, Experience in full life cycle Hadoop Solutions: requirement analysis, platform selection, design future state application and enterprise architecture, testing and deploying solution, Expert knowledge in modern distributed architectures and compute / data analytics / storage technologies on AWS, Knowledge of a programming and scripting languages such as Java/Python/Perl/Ruby/linux, Understanding of architectural principles and design patterns using frameworks such as Hadoop / Spark and/or AWS EMR, Knowledge of SQL ( MS SQL, PostgreSQL, mySQL) and NoSQL databases (HBase, DynamoDB, Cassandra), Knowledge of technical solutions, design patterns, and code for applications in Hadoop, Experience in architecting and building data warehouse systems and BI systems including ETL (Inofmratica, Talend), Software Development Lifecycle (SDLC) experience, AWS Architecture / Azure Architecture experience ideally with the appropriate vendor certification, Understanding of hybrid cloud solutions and experience of integrating public cloud into tradition hosting/delivery models, Experience as principal technical lead on at least one major project, AWS or Azure trained / certified architect – e.g. Such elements also provide great discussion points during an interview - they will help recruiters know how to approach you and make the conversation easier. Big Data Architect Resume Sample. When a person of science thinks about publications, they immediately default to research papers published in reputed peer-reviewed journals. Create a resume to be proud of with Enhancv. BI) through technical solution deliverables, Create, maintain and update development standards, process and product methodology, You are responsible for the design of software on component or module level, You have a deep understanding of the consequences of your design on the architecture, You are responsible for communicating effectively the consequences of your design on the architecture, You will design software, on the basis of design specifications in accordance with the functional specifications, You will finalize the design specifications, code and test the designed modules or components, so that the software in question will be reliable, efficient, easy to maintain, and user-friendly, Perform work in line with the product development or software engineering processes that have been agreed in the department, Primary and Lead Data and Solution Architect on a project. The experience section is the meat of your resume. Big Data Engineer Resume. A resume objective is great for an entry-level data scientist who wants to show their passion for the subject and to prove their motivation. You can always email the company’s HR department to ask about their policies before you apply. The reason is simple - a good data scientist is not just a numbers person. Menu Close Resumes; Articles ; Menu. Resume summaries are a great way to share a condensed version of your professional (and personal) story. No spam, just information that will help you build a resume that makes you feel relevant and well represented. For your data scientist resume, you want to pay special attention to the second point focused on your experience. Find that Data Analyst job in Lake Success with the myperfectresume Job Search Engine "It gave potential employers more insight into who I am and whether I was a personality fit for their team. Data lakes and data warehouses are both widely used for storing big data, but they are not interchangeable terms. Your passions and interests outside of work; Showing you know your stuff by presenting relevant education and certificates; Demonstrating practical knowledge with experience and projects you’ve worked on; Showing how your skills align with the requirements in the job description; Adding a pinch of personality with additional sections. Add a couple more - the ones you think are your differentiating strengths. - Select from thousands of pre-written bullet points. 20+ examples and tips from our experts. Generally, data from a data lake require… Knowing the technical stuff often doesn’t cut it. Condensed - for senior data scientists, the main challenge is how to fit everything - rich experience, numerous skills and certifications - into one or two pages. This will need you to be hands on to build in quick prototypes/proof of concepts, Work with the operations team to build systems, process and team required to run and maintain the systems securely, reliably and in a scalable manner, Good understanding of infrastructure including server sizing, Experience in database design/implementation; Version Control systems such as GIT, CVS or Subversion (SVN), Strong debugging, troubleshooting, and diagnostic skills, Passionate about solving problems, quality and learning new technologies, Participate in an ongoing partnership with the business to apply in-depth knowledge of the business operations, strategies, priorities and information requirements to establish the technical application direction, Define the system, technical, and application architectures, and in some instances the business systems/process architecture for major areas of development, with a focus on application architecture, Ensure appropriate technical application standards and procedures are defined, Ensure best practices are adhered to in the adoption of new application technologies, Research, evaluate and select application technologies (existing or emerging) that best fit business and IT strategic needs, Ensure the delivery process and technology strategies are coherent and optimized, Participate in developing and architecting application solutions in a multi-project, collaborative environment, Design and assist with the delivery of proofs-of-concept for new or improved enterprise-wide technologies that are used across multiple areas of the business, Architect application solutions across multiple hardware/software computing environments and system components; and, Plan and implement process re-engineering or process improvement, Must have 7+ years of application design, development, and architecture experience using Microsoft .NET platform or Java/J2EE technologies, 3+ years of hands-on experience with the technologies in the Hadoop ecosystem like Hadoop, HDFS, Spark, MapReduce, Pig, Hive, Flume, Sqoop, Cloudera Impala, Zookeeper, Oozie, Hue, Kafka, Extensive knowledge of application architecture, design, and development, Extensive knowledge and experience with Big Data Architecture, Distributed Architecture, MicroServices and EAI/EI, Extensive knowledge of various technology architectures and hardware platforms, both existing and emerging, Working knowledge of EA methodologies and tools, including TOGAF or Zachman architecture frameworks, Working knowledge of relational and dimensional database concepts, Must be a methodical and pragmatic problem-solver, Must have a strong sense of teamwork, active listening skills and negotiation and influencing skills; and, Leading all technical aspects of the project including interfaces, At least 3 years experience designing/developing/delivering architecture/infrastructure/data integration/data management support environments including virtualized systems environment, Big Data databases, security and portals, At least 3 years experience providing technical leadership on projects, At least 3 years experience creating transition plans, At least 3 years experience implementing SBMC2, At least 8 years experience designing/developing/delivering architecture/infrastructure/data integration/data management support environments including virtualized systems environment, Big Data databases, security and portals, At least 8 years experience providing technical leadership on projects, At least 8 years experience creating transition plans, Identifies discrepancies between the enterprise technical architecture and systems designs proposed by project teams, and assist project teams in resolving the discrepancies, Designs real-time software applications on selected platforms, Acts as an advisor to SPAWAR and DHA system engineers and proposes changes to the enterprise technical architecture based on analysis of requirements and new technology, Expert in ETL design and implementation and direct teams, Analytical and technical skills with the ability to analyze issues, assess technical risks, and deliver sound solutions in a timely manner, Expertise ITIL process in incident management, problem management, change management and release management, 8+ years of experience supporting big data platforms with exposure to the latest technology in in Big Data, Master Data Management (MDM) and Data Quality Services, Experience with MHS and/or VA data and analytical uses, Experience working with dashboards, visualization and reporting front end, Experience with various BI tools such as Tableau, SSRS, SSAS, SAS, etc, Expert in relational database concepts and SQL, Exposure Strong leadership skills, decision making and problem solving abilities, Experience with CMMI Level 3 delivery is a plus, Design and Build world class high-volume real-time data ingestion and processing frameworks and advanced analytics on big data platforms, Data Management strategy defining direction of data organization; metadata management within Data Lakes, Research, develop, optimize, and innovate frameworks and patterns for enterprise scale data analysis and computations as part of our big data and Internet of Things initiatives, Lead the implementation of Hadoop Data model strategy by creating architecture blueprints, validating designs and providing recommendations on the enterprise platform strategic roadmap, 3+ years of hands-on implementation experience working with a combination of the following technologies: Hadoop distributions, Storm and Spark streaming, Kafka, Spark advanced analytics, NoSQL data warehouses such as Hbase and Cassandra, data processing frameworks like Apache Nifi, Talend, Spring XD, 1+ years’ experience in designing and implementing big data solutions. 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