data engineer and data analyst resume

data engineer and data analyst resume

A data analyst resume example better than 9 out of 10 other resumes. Possessing strong technical skills rooted in substantial training as an engineer. Guide the recruiter to the conclusion that you are the best candidate for the market data analyst job. Design, architect, implement, and support key datasets that provide structured and timely access to actionable business information with the needs of the end customer always in view. ), Global mindset with ability to effectively work on distributed remote teams, Experience / familiarity with Remote Monitoring & Diagnostics, Expertise in one or more analytics software tools and packages e.g. and using databases in a business environment with complex datasets, Ability to take loosely defined business questions and translate them into clearly defined technical/data specifications for implementation, Designing distributed computing systems to support data science initiatives including descriptive, predictive, and prescriptive analytics, Assess, document, and translate goals and problem statements into use cases for engineering development and implementation, BS or higher in Computer Science / Software Engineering, 6+ years software development experience, preferable in data analytics/science space, Good knowledge of Big Data frameworks, concepts, and tools such as Hadoop, HDFS, Hive, Language / Tools / API Experience: Java/J2EE, JS, JQuery, JSON, Bash, Python, Git, Linux/Unix, Experience in designing and querying SQL & NoSQL databases such as PostgreSQL, MySQL, Oracle, Couchbase, Experience with building stream-processing systems using solutions such as Storm or Spark-Streaming, Knowledge and experience in: Big Data ML toolkits, such as Mahout, SparkML, or H2O Cloud computing ecosystems including Amazon Web Services, BigQuery, Azure, etc, Messaging systems, such as Kafka or RabbitMQ, Take direction but also work autonomously, Ability to work effectively on fast-paced, short-deadline projects, In this role, you will have the opportunity to display your skills in the following areas, Design, implement, and support a analytical platform providing ad hoc access to large datasets and computing power, Managing AWS resources including EC2, RDS, Redshift and etc, Explore and learn latest technologies to provide, At least 3 years of relevant work experience in analytics, data engineering, business intelligence or related field, Demonstrable ability in data modeling, ETL development, and Data warehousing, or similar skills, Demonstrable skills and experience using SQL with large data sets (e.g. A comprehensive resume can help you land top data analyst jobs, says resume expert Kim Isaacs. 2+ years of relevant experience as a data engineer, Experience in using databases in a business environment with large-scale data sets, Experience in gathering requirements, formulating the right data models and access tools when building comprehensive data decks, Experience with data visualization software, A Bachelor’s Degree in Computer Science, Mathematics, Statistics, Finance or related technical field, Experience in data extraction, transformation, statistical analysis, predictive modeling, Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift, Excellent knowledge of Oracle SQL, Linux, Amazon Redshift, Knowledge and direct experience using business intelligence reporting tools. We are looking for someone who is keen on leveraging their existing skills while applying new approaches to the Data Solutions, Create and maintain systems to load and transform very large data sets from digital media retailers (iTunes, Spotify, YouTube, etc) as well as social media sources, Work with a cross-functional team to create data-driven insights and reports for business stakeholders, Work with the Software Engineering team to create customer-facing analytics tools and visualizations, Experience with AWS ecosystem. DEF COMPANY [Startup in the payment processor space] — Sometown, WA No need to think about design details. Customize this Resume. to enhance useful analytic opportunities and influence customer content and experiences, Develop and monitor batch Hadoop data and query processes and apply Spark, Spark Streaming, and other evolving tools to improve toward central unified real-time logging and microbatching, Research and monitor data quality and issues via structured and unstructured query languages (SQL, ElasticSearch/Kibana, etc. Implements database concepts and practices including definition and query language, Prepares project plans and uses flowcharts and data flow diagramming to create program design concepts, Creates detailed system design documentation, Analyzes requirements and architecture specifications to create detailed design, May provide technical advice and training and mentor other associates in a lead capacity, Six years of experience with SQL Server as a Database Platform, Six years of working experience with ETL concepts and building ETL solutions, Six years of Mid to Senior level experience in Oracle database concepts and Oracle-SQL, Six years of experience with ETL Tools such as ODI, Informatica, Proficient in Data warehousing concepts and up to date Data Integration patterns/technologies, Experience with prototyping & automating Data Integration Processes, Experience with Physical Performance Optimization of SQL Server Databases, Understanding of Master Data Management (MDM) principles is a plus, Good written and verbal skills are required, Bachelor’s Degree in a Technology Related Discipline is preferred, Experience with MySQL in a large-scale, high-traffic environment, Complex SQL statement writing, Scripting language programming $, Three years of experience with Oracle Data Integration-ODI, Two years of experience with ETL(Extract Transform Load), Build and execute analytics and reporting across platforms to identify user behavior and analyze trends, patterns, and shifts in user behavior, both independently and in collaboration with product managers and data analytics resources, Develop best practices for configuring analytics technology, for analyzing user behavior on multiple platforms, and for collecting and interpreting data from multiple sources, Develop experimental data models/ designs to help answer unforeseen questions that will influence decision-making in a rapidly changing business environment, Communicate technical results to a wide variety of audiences, Bachelor's degree in a quantitative field (e.g., Mathematical, Statistics etc. There are many steps to a successful job search, but no matter what industry you're in, the first step is the same: having a solid, organized resume that will attract hiring managers. Spark and Kafka would be advantageous, Proficiency (Mastery level) in Python and/or Java, Hive, Experience of design focussed development, Responsible for administration (i.e. Oracle, SAP), Strong customer service mindset, with the ability to build, maintains, and enhance relationships, Bachelor's degree in computer science or a related technical field, 4+ years of relevant employment experience, Experience operating 100TB+ Data Warehouses, Exposure to NoSQL technologies (EMR/Hadoop, Spark, Hive, Parquet, etc. Java, Scala, Python), Expertise in Apache Hadoop ecosystem related Apache open source projects, Solid knowledge of database programming (SQL), Strong interpersonal, written and verbal communication skills. We are always working on our own projects too, dreamed up inside the team, to improve the product, Extensive experience in JavaScript and other client-side technologies, Excellent knowledge of data structures, algorithms and design patterns, Experience developing dashboards and generating insights, Knowledge of working with content management systems, Ability to work independently and collaboratively within a team, Experience with distributed data processing system, such as Hadoop/MapReduce, Hive, Pig and SQL/NoSQL databases is a plus, Work with business and technology partners to provide reporting capabilities for all our internal customers, Design and develop SQL scripts and tools to serve specialized analytics requests, Work with data scientists and analysts to develop innovative techniques for capturing event driven data to enable real-time decision-making and response, Institute continuous integration methodologies as a part of solution design, Work on all phases of projects from design to implementation including specifications, development, testing, rollout, documentation and, if applicable, turnover to the Maintenance Engineering and Operations Team, Work within state of the art engineering practices (i.e. Developed insights into the performance of Network/Studio programs and their competitors across all platforms (including linear, multiplatform and SVOD) IBM, Data Scientist. Basic experience in modeling dimension tables with SCD1 and SCD2 attributes, snowflake dimensions, junk and degenerate dimensions; bridge tables; transaction facts, accumulating and periodic snapshot facts; reference and master tables; transaction tables; staging and lookup tables in an EDW environment, Three (3) years’ experience in performing data profiling and data analysis on source system data to determine the actual content, structure and quality of data, 5+ years of related work experience in Data Engineering or Data Warehousing, Proficient in building and maintaining robust ETL jobs (Talend, Pentaho, SSIS, Alteryx, Informatica, etc. ), SQL/Hadoop skills with ample experience handling large datasets, Develop a deep understanding of AWS’ vast data sources and know exactly how, when, and which data to use to solve particular business problems, Bachelor’s degree in CS or related technical field and 6+ years of experience in data warehousing, 4+ years of relevant experience with ETL, data modeling, and business intelligence architectures, Experience building self-service reporting solutions using business intelligence software (e.g.OBIEE, Tableau Server, etc. Tableau, QlikView, and MicroStrategy), A proven record of managing project plans and collaborating across geographies and functions, Passion for Maps, Geospatial Analysis and Mapping, Expertise in building and maintaining reliable ETL jobs, Proven ability to work with varied forms of data infrastructure, including relational databases (e.g. Data analyst focuses on data cleanup, organizing raw data, visualizing data and to provide technical analysis of data. How to describe your experience on a resume for a data analyst to get any job you want. Oracle, SQL Server, and others okay, Programming Languages: SQL, QUEL, FORTRAN, VBA, Productivity Applications: Access and Excel. Get noticed today! Take project and task ownership and drive them to completion, Support the team products operationally. specialized UDFs) and analytics applications, Employ a variety of languages and tools (e.g. Flinders … Exceptional candidates considered with Bachelor’s degree or Master’s degree in progress, Strong programming experience with: Python, Java, SQL, Ruby and other scripting languages, Proven experience building and maintaining data flow systems in AWS, Proven experience modeling and querying NoSQL, such as DynamoDB/ MongoDB, Proven experience architecturing big data solutions, such as AWS EMR/S3/EC2/HDFS/Hadoop, Proven experience with building and deploying ETL pipeline, Proven experience with emerging big data technologies, Proven experience with relational databases and SQL, Plus- experience with one or more specialize areas: deep web, image and remote sensing data, natural language data, geospatial data, Design and implement systems to either manually or automatically download data from websites and parse, clean and organize the data, Research opportunities for data acquisition, Assess and resolve data quality issues and correct at source, Ensure all data solutions meet business requirements and industry practices, Have extensive experience in employing a variety of languages and tools to marry disparate data sources, Have knowledge of different database solutions (NoSQL or RDBMS), Have knowledge of NoSQL solutions such as MongoDB, Cassandra, etc, Work effectively both in a local server environment and in a cloud-based environment, Collaborate with Data Architects and IT team members on project goals, Collaborate with Data Scientists and Quantitative Analysts, Master’s degree in a data intensive discipline (Computer Science, Applied mathematics or equivalent) is strongly preferred, with a background in “big data” computer programming and/or a minimum of 3-5 years experience in “big data” processing. Big Data Engineer Resume – Building an Impressive Data Engineer Resume Last updated on Nov 25,2020 23.1K Views Shubham Sinha Shubham Sinha is a Big Data and Hadoop expert working … By continuing, you agree to Monster's privacy policy, terms of use and use of cookies. Maintains a broad understanding of Vanguard’s technologies, tools, and applications, including those that interface with business area and systems, Designs and conducts training sessions on tools and data sources used by the team and self provisioners. You’ve built the applications and web services that rely on the data too. You know acronyms like REST and SOAP just as well as PK and FK, Synthetic data modeling and metadata management with some experience in the concepts of master data management (MDM) and enterprise information integration (EII.) In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP), This position requires a Bachelor's Degree in Computer Science or a related technical field, and 8+ years experience, Experience with ETL, Data Modeling, and working with Business Intelligence systems, Experience with processing large, multi-dimensional datasets from multiple source, Experience in monitoring and automated reporting, MS or PhD in CS or another quantitative field, Experience processing large, multi-dimensional datasets, Experience with Java and Map Reduce frameworks such as Hive/Hadoop/Spark, Someone who is keen to leverage their existing skills while trying new approaches, 1 year experience developing ETL/ ELT solutions within a Data Warehouse environment, 1 year of experience in using SQL, PL/SQL, Shell scripting, Strong critical thinking and attention to detail, Experience in big-data using Hadoop, Hive, and other open-source tools/technologies, Experience in designing and building large data warehouse systems, Good working knowledge of Oracle environment, Good work experience in BI Reporting tools and databases in a business environment, Minimum of 3 years software development experience, 1 + year experience working with traditional, SQL-oriented database techniques and technologies, 1+ year working with Hadoop or related technology, Ability to work with high volume heterogeneous data, preferably with distributed systems such as Hadoop, Experienced with batch and real-time data processing frameworks like Crunch, Scalding, Storm, Kafka, or Spark, Knowledgeable about data modeling, data access, and data storage techniques, Experience with agile software processes, data-driven development, reliability, and responsible experimentation, Experience working on open source or other data-related projects, 5+ years Business Intelligence related experience, Excellent Knowledge of Data Warehousing and ETL, Excellent knowledge of SQL and Scripting languages, Broader understanding of BI technologies and choose the right technologies according to the use case, Experience of BI visualization tools (tableau, OBIEE, MicroStrategy, etc. Conduct code reviews, Collaborate with other IT disciplines, including Requirements Engineering, Data Analysis, Quality Assurance, and Project Management to review project plans, requirements documentation and test plans, Be the focal point person leading the effort for troubleshooting software engineering related issues in solutions, Proactively identify and communicate risks and issues to management and create action plans to mitigate risks, Work on strategic initiatives on technology selection, research and development and process improvement, Create and maintain logical and physical data models for Retirement Planning in support of application development, Serve as the primary application DBA to establish reference data models, processes, and data mappings, transformational rules to support real time and batch data integration, Provide technical guidance to the application developers and DBAs to diagnose and optimize query performance, 6+ Years demonstrated experience designing software solutions using varied design and/or modeling techniques such as object models, class diagrams, component diagrams, sequence diagrams and tools such as UML, Visual Paradigm, 4+ Years developing with core Java technologies OR C# .NET, C++, 4+ Years experience with HTML, XML, SQL, PL/SQL and REST/SOAP-based web services, 4+ Years experience developing to database designs and standards, including Oracle, SQL Server, MySQL, 4+ Years of experience in developing SQL, DDL, DML and vendor specific data programming language such as PL/SQL or Transact SQL, 4+ years of experience applying data modeling techniques and tools such as ERWIN and/or other modeling tools, 4+ years of experience in data analysis, including developing relational and multi-dimensional database and cubes, Strong experience with the Oracle DBMS environment, 3+ Years in a variety of software methodologies agile, scrum, waterfall, RUP, An analytical and collaborative mindset that allows you to delve into technical issues both as an individual contributor and as part of a team to understand not only how something works, but why it works, and how it can be improved, A demonstrable understanding of common security threats and mitigation strategies, A bachelor’s degree in Computer Science or related field and 5 years of experience as Software Engineer, or the equivalent combination of education and/or experience, Experience with mainframe technology including JCL, VSAM, Cobol, Experience with Microsoft SSIS, SSAS, SSRS, Experience with MS SQL server, DB2, XML/XSD and TOAD, Experience with FIS/Sungard Omni Suite of products, Experience with technology roadmap development and project management principle/concept, Understanding of the financial services industry, specifically retirement planning and/or individual annuity, Some experience working with financial data, Excellent analytical, mathematical and problem solving skills, Strong initiative and a thirst for knowledge in finance, business or accounting are required, Excellent interpersonal and communication skills with the ability to work efficiently in a fast-paced environment on multiple concurrent projects, Some database experience (SQL, DDL/DML, performance tuning, data modeling), Exposure to one or more scripting languages - Perl / Python / JavaScript, NoSQL / Distributed data store technologies like HDFS, Apache Cassandra, Working with structured/un-structured data, file parsing, web scraping, Good understanding of UNIX/LINUX environments, Design and build high-scale, batch and real-time data processing pipelines using Big Data technologies including Hadoop, Spark, Kafka and relevant platforms, Build, verify and deploy machine learning models, Continuously improve productivity and sustainability with great coding, QA and release practices, coaching less-experienced team members, Five (5) years’ experience in design and development of clear, standard and performant SQL code on Oracle 11g, Teradata 14.10, and SQL Server 2012 database platforms by joining tables, filtering rows, transforming columns, grouping, ordering and sorting data, utilizing analytic functions, pivoting and unpivoting data, Five (5) years strong experience in creating database objects, schemas, tables, views, stored procedures, indexes, synonyms, and materialized views in Oracle 11g, Teradata 14.10, and SQL Server 2012, Five (5) years’ experience in design and development of complex KSH shell scripts on UNIX, Linux, and Windows server environments in order to modify, copy, rename, move, schedule, and process flat, complex flat, XML, csv, and delimited files, Five (5) years’ experience using Data Stage 8.7 to design and develop efficient, effective, and complex EDW data integration mappings using the following stages: sequential file, data set, file set, complex flat file, oracle enterprise, ODBC Enterprise, DB2/UDS Enterprise, Teradata, SQL Server Enterprise, Aggregator, FTP, Filter, Funnel, Join, Lookup, Merge, Modify, Remove Duplicates, Slowly Changing Dimension, Sort, Transformer, Surrogate Key Generator, Sequencer, Job Activity, Notification and Exception Handler, Three (3) years’ experience in dimensional modeling and entity relationship modeling at conceptual, logical and physical levels.

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