Lexicon Solutions’ Post

Hiring Alert ‼️ Northern Trust is hiring for Data Engineers with 3+ years of experience. ✅Direct apply link: https://lnkd.in/gNn-VeYk Stay tuned here Mahesh Gore for more such Data Engineering / Data Analyst related content!! ⚡️Join our telegram community for daily updates, Link in the comments⚡️ #dataengineering #bigdata #jobs #vacancies #datascience #dataanalytics #dataanalyst #dataengineer

Unclear data engineering job description? Are you wondering what responsibilities fall within a data team? Then this post is for you. In this post, we go over the six key duties of a data engineer. The number of these responsibilities you may handle depends on your company and team. Teams in smaller companies generally handle all six responsibilities, whereas larger-sized companies may have individual(or multiple) teams handling one(or a mix) of these responsibilities. https://lnkd.in/eqcKcZQ What are your responsibilities? Are they too much or too little? Let me know in the comments below! #dataengineering #datajob #datapipeline #data

Factors to Consider While Hiring a Data Engineer Consultant in 2024 https://lnkd.in/gvHc35X9 #Dataengineeringconsulting #dataengineerconsultant #dataengineerconsultancy #dataengineeringconsultancy In this article we will explore several factors to consider while selecting a data engineer consultant in 2024.

https://lnkd.in/d2kfyn3G Job Overview You will be part of a world-class Data Science team that leverages data to drive insights about our products and customers. The Data Science team partners closely with Product Managers/Engineers/Researchers/Data Engineers/Marketers/Privacy and Executive teams across to drive and influence. The team is responsible for using a variety of analysis and data-science techniques to understand how customers engage with our products and communications and, in doing so, identify, design, and measure the success of product investments. In this role, you will: Collaborate on a variety of product and business problems with a diverse set of cross-functional partners, become a trusted strategic partner, and build credibility through the structure and clarity of your work. Apply technical expertise with quantitative analysis, experimentation, and the presentation of data to develop strategies for our business and help solve the business’s biggest challenges. Focus on developing hypotheses through analytical approaches, different methodologies, frameworks, and technical approaches to test them. Define, understand, and test opportunities to improve the products and business and influence roadmaps through insights and recommendations. Partner with cross-functional teams to inform, influence, and execute strategy decisions Identify and measure the success of product efforts through forecasting and monitoring of key product metrics to understand trends. You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Atlassian. You will use storytelling techniques to communicate insights broadly, including to company leadership teams. Minimum Qualifications / Your background: 8+ Years of Experience in Data Science or related fields Proficiency in SQL AND another data manipulation programming language (e.g Python, R) Expertise at telling stories with data and familiarity with at least one visualization tool (e.g. Tableau, R-Shiny, Microstrategy, SAP Business Objects, Looker, etc.) Expertise in applying a broad variety of statistical concepts (e.g. regressions, A/B tests, clustering, probability) to business problems and a strong sense of when to adapt/combine approaches to suit the problem at hand Experience driving projects or programs which have had proven impact on business strategy and performance through your analytics skills A proven track record for crafting analysis into well-written and persuasive content Experience advising, presenting to and serving as a thought partner to senior executives Desirable Qualifications 10+ Years of Experience in Data Science or related fields An understanding of the SaaS business model and key metrics #AlbionarcJobs#FintechJobs #AsiaJobs#MiddleEastCareers #TechTalent#FintechRecruitment

Factors to Consider While Hiring a Data Engineer Consultant in 2024 https://lnkd.in/eEmTxE7w #Dataengineeringconsulting #dataengineerconsultant #dataengineerconsultancy #dataengineeringconsultancy In this article we will explore several factors to consider while selecting a data engineer consultant in 2024.

Are you in search of an experienced and passionate data engineer to lead your data initiatives to success? Look no further! My expertise lies in building scalable data architectures and optimizing data workflows. Let's connect and discuss how we can chart a path to greatness together. #dataengineer #ETL #data #dataanalysis #DataExtraction #DataInnovation #DataAnalytics #TechJobs #Hiring #DataRevolution

#hiring Data Engineer, Denver, United States, fulltime #jobs #jobseekers #careers #Denverjobs #Coloradojobs #Engineering Apply: https://lnkd.in/g7wwnYkf Job Description The data engineer will serve as a liaison between its core developers and downstream analysts. The data engineer's primary job is to code automated processes that extract data from disparate sources; efficiently build and manage transformations into a cloud data warehouse; and build pipelines that load data into tools used by economists, data scientist, data analysts, and many other stakeholders. SQL and Python/R skills are a must. Experience managing data warehouses and ELT/ETL processes in an OLAP database is strongly desired. The employee can be in the U.S., Canada, Belarus, or Poland. Job Responsibilities Move data between systems: Extraction - Appcast has several disparate internal proprietary, external proprietary and external public sources that all serve our customers in several ways. A data engineer's primary job is to build automated processes that extract data from these disparate sources for downstream use by data analysts. Transform - A data engineer will transform data from disparate sources into distinct tables using a relational data model, so that analysts can pull them together in one unified workflow. Load - A data engineer will need to load the new tables into a cloud data warehouse using efficient, low-latency methods. Manage cloud data warehouse: Monitor performance - As data needs grow, the data engineer will need to monitor essential performance queries used by downstream analysts to ensure data is being delivered in a timely manner that does not cause slowdowns. Data quality - Ensuring both internal and external data sources are accurate and up to date to provide the best quality for our clients and media partners. Serve data to downstream users

#hiring Data Engineer, Denver, United States, fulltime #jobs #jobseekers #careers #Denverjobs #Coloradojobs #Engineering Apply: https://lnkd.in/g3fD7VY3 Job Description The data engineer will serve as a liaison between its core developers and downstream analysts. The data engineer's primary job is to code automated processes that extract data from disparate sources; efficiently build and manage transformations into a cloud data warehouse; and build pipelines that load data into tools used by economists, data scientist, data analysts, and many other stakeholders. SQL and Python/R skills are a must. Experience managing data warehouses and ELT/ETL processes in an OLAP database is strongly desired. The employee can be in the U.S., Canada, Belarus, or Poland. Job Responsibilities Move data between systems: Extraction - Appcast has several disparate internal proprietary, external proprietary and external public sources that all serve our customers in several ways. A data engineer's primary job is to build automated processes that extract data from these disparate sources for downstream use by data analysts. Transform - A data engineer will transform data from disparate sources into distinct tables using a relational data model, so that analysts can pull them together in one unified workflow. Load - A data engineer will need to load the new tables into a cloud data warehouse using efficient, low-latency methods. Manage cloud data warehouse: Monitor performance - As data needs grow, the data engineer will need to monitor essential performance queries used by downstream analysts to ensure data is being delivered in a timely manner that does not cause slowdowns. Data quality - Ensuring both internal and external data sources are accurate and up to date to provide the best quality for our clients and media partners. Serve data to downstream users

Data Architect opportunity with international NGO