Intro to Data Analysis Workflows in Python with Pandas
Free Live Workshop on April 22 at 11am Eastern - Register Now
Data engineers create data pipelines that take raw data and transform it into a format that is clean, consistent, and actionable by analysts and data scientists. They play a critical role in maintaining the data assets of an organization and helping to put data models into production.
Python, SQL, and Apache Spark
Cloud Computing, Data Analysis, and Databases
Percent of recent job postings including a given data tool
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At Intel, we are innovating the future. We create world-changing technology that enables global progress and enriches the lives of every person on earth. Today, we stand at the brink of several technology disruptions – driven by four key “superpowers”: cloud, mobility fueled by 5G, artificial intelligence (AI) & machine learning, and the intelligent edge. Intel is at the heart of these disruptions defining the art of the possible. The Corporate Strategy Office (CSO) at Intel defines, develops, and leads the implementation of new strategies to harness the power of industry-shaping disruptions and to transform Intel into a datacentric company.
The Corporate Strategy Data Science and Strategy Analytics function within CSO plays a critical role in developing the ground truth market models and insights upon which corporate strategy is developed. In deep partnership with other market analysis centers of excellence within the company, we ask and answer the critical market questions that inform our strategic choices. We are building a world-class analytics practice with both top and bottom-line impacts.
We are looking for a Data Scientist/Translator who can contribute to the development of forecasts, models, and analytics. You will keep one foot solidly planted in the data science/engineering activities of the organization while also interfacing with constituents and coordinating activities at the intersection of model development and business strategy.
Own visualization and communication of analytics for the group, including the development of visual assets and BI dashboards.
Be a custodian of data models and infrastructure.
Collaborate with team members on the data science underpinning forecast and insights platforms.
Partner with other centers within the company to elevate the visibility and impact of market. modeling and insights work.
As needed, contribute to important strategy projects resulting in actionable recommendations.
Communication skills (written and verbal), including the development of novel visuals and infographics
Hypothesis-driven, problem-solving orientation with ability to leverage both quantitative and qualitative analyses to drive decision making
Skills in peer influencing, indirect leadership, and cross-group collaboration skills including demonstrated impact in communicating complex information to executive leadership in a manner that leads to strategic action.
Experience working with geographical diverse teams.
Results driven and accountability for broad leadership, building of followership and role modeling of Intel's cultural attributes of:
Customer obsessed - seek to understand what matters most to our customers, listening more and talking less.
One Intel - "we" before "me". We work across boundaries, collaborating across the aisle and around the world.
Fearless - We are bold. We take risks and challenge ourselves. We fail fast, iterate and continuously improve.
Truth and Transparency - allows the best ideas to emerge and speeds our ability to solve problems faster.
Inclusion - Inclusion runs through each attribute and is integral to our culture evolution.
You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. This position is not eligible for Intel immigration sponsorship.
Bachelor’s degree in data science or related field.
5+ years of experience in the following:
DevOps experience (including Azure DevOps and GitLab) managing staging and production environments and delivering continuous improvement in the team’s workflow.
Data modeling (Dimensional, Normalized, Key-value pair), information architecture, analytics, schema evolution, data organization/layouts.
Experience building econometric models and forecasts from both third party and primary research/data sets - preferably at a top tier consulting and/or market analytics firm.
Development and implementation of models, algorithms and applications that apply mathematics to data and solve a variety of business problems.
Expertise in some aspect(s) of the semiconductor industry from manufacturing through foundry services, architecture, and design/engineering.
Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse, open platforms that unify data warehousing and advanced analytics. The Data Engineer will help us leverage the Lakehouse architecture for our own internal customer success and field engineering data.
You will work with the different data analytics team to build clean datasets in Databricks and publish them on Tableau Online for analysis. Understanding and building the customer success and field engineering technology stack and how the data flows between systems (Salesforce, lakehouse) is crucial. You have experience writing ETLs, communicating technical requirements to the business, and understanding basic customer success, field engineering business logic. The Data Engineer will become an expert on using the Databricks platform for data and AI purposes. You will report directly to the Data Science Manager.