דרושים Data Engineering Leader Analytics ב-Facebook ב-ארהב

Plan, direct, and coordinate activities and proactively drive the vision for Bl and Data Warehousing across a product vertical.

Build a high-quality Bl and Data Warehousing team and design the team to scale.

Manage data warehouse plans across a product vertical.

Define the processes needed to achieve operational excellence in all areas, including project management and system reliability.

Build cross-functional relationships with Data Scientists, Product Managers and Software Engineers to understand data needs and deliver on those needs.

Drive the design, building, and launching of new data models and data pipelines in production.

Manage development of data resources and support new product launches.

Drive data quality across the product vertical and related business areas.

Manage the delivery of high impact dashboards and data visualizations.

Define and manage SLA's for all data sets and processes running in production.

Requires a Master's degree (or foreign equivalent) in Computer Science, Information Systems Management, or a related technical field and 96 months of experience in the job offered or in a related occupation. Requires 96 months of experience involving the following:

1. Scaling and managing 5 person teams

2. Project Management Leadership experience initiating and driving projects

3. Data architecture in designs, builds and contributes to services that reduce the complexity and time investment required to log data accurately and efficiently and architects sophisticated multi tier logical and physical models that reduce the time and complexity required to perform data modeling across a product or domain

4. SQL or similar languages and development in at least one scripting language such as Python and Perl

5. Data pipelines in evaluates design and operational cost benefit trade offs in systems evaluates configuration parameters to optimize efficiency, performance and scalability of software components, partners with system architects to optimize design to deliver the overall system architecture architects and implements for scale and complexity and defines and evolves new standards and patterns that are adopted across the function

6. Data visualization in designs and builds services that reduce the complexity and time investment required to prepare and manipulate data for visualization, appropriately applies advanced concepts and procedures to solving complex data visualization problems identifies and creates the most powerful way to visualize the data and distills complex findings into simple, compelling visualizations and conceptualizes new interface components, widgets and design elements, or new ways to compose an interface to maximize its value and usefulness

Manage cross-functional IT project teams to lead the ideation, development and launch of technologies and processes to support our data center supply chain and logistics.

Manage multiple business analytics projects through prioritization, planning, scheduling, reporting and influencing.

Identify ways in which new technologies can provide new functionalities and better user experiences.

Gather and prioritize stakeholders’ requirements to build, maintain and implement roadmaps.

Work with systems analysts and software engineers to automate key processes, fix gaps, and build reporting capabilities.

Contribute to strategic decisions with the product and executive teams.

Bachelor's degree in Computer Science, Information Technology or a related field and 60 months of experience in progressive, post-baccalaureate experience in the job offered or in a computer-related occupation. Foreign equivalent accepted

Requires 60 months of progressive, post-baccalaureate experience involving the following:

1. Industrial engineering, supply chain management, and/or information systems

2. Supply chain and logistics functions, including material planning, asset management, inventory management, and transportation

3. Handling program manager responsibilities including prioritization, planning, scheduling, and status reporting

4. Agile methodologies and technical understanding of and experience with developing relationships with software engineering/IT teams

5. Spreadsheet modeling and database capabilities and

6. Gathering and analyzing data/information to address complex problems

Lead mechanical engineering projects for the Facilities infrastructure Operations team, including working cross functionally with design teams, construction, field operations, vendors, and R&D.

Troubleshoot and establish corrective actions for designs and implementation.

Conduct regular analyses and audits of mechanical system utilization.

Develop effective measurements and reports from BMS and other monitoring systems to increase performance and reliability.

Evaluate systems to perform effective and efficient load management and capacity planning.

Monitor, trend, and develop engineering metrics and statistical data for strategic planning.

Review “asbuilt” mechanical documentation and verify accuracy.

Investigate actual site conditions and update records.

Develop and generate specifications, RFPs, ROMs and SOWs for projects.

Evaluate facility processes and industry best practices to drive efficiencies and effectiveness.

Requires a Master's in Mechanical Engineering or a related field and two years of work experience in the Job offered or in a related occupation

Requires 24 months of experience involving each of the following:

1. HVAC systems design

2. Chiller operation and troubleshooting

3. Air movement fundamentals

4. HVAC system component sizing

5. HVAC&R Controls and troubleshooting

6. ASHRAE and UL standards and

7. Heat exchanger and heat transfer fundamentals

Plan, direct, or coordinate activities in such fields as electronic data processing, information systems, systems analysis, and compute r programming.

Be both a highly technical, and aneffective people manager.

Be a subject matter expert in at least one specific domain.(examples: product, product infrastructure, infrastructure, machine learning).

Lead teams that deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area.

Work with team and cross functional partners to define and influence strategy.

Work on issuesrequiring an in-depth knowledge of organizational objectives.

Drive roadmap creation and execution.

Collaborate with various functions, drive engineering initiatives and have an impact at an organizational level.

Participate in technical design.

Measure the impact of team and set clear expectations and goals.

Manage activities of two or more sections or departments,supervising costs, methods, and staffing.

Work effectively with cross functional partners and stakeholders to set and achieve optimal outcomes.

Partner with leadership to influence anddrive org design, contribution and prioritization.

Requires a Master’s degree (or foreign equivalent) in Computer Science, Computer Software, Computer Information Systems, Engineering, Applied Sciences, Mathematics, Physics or related field and 1 year of experience in the job offered or in a computer-related occupation

Requires 1 year of experience in the following:

1. Software engineering work experience including hands-on technical management building infrastructure core components

2.Coding in one of the following languages: C++, Java, JavaScript, Python, or PHP

3. Architecting, developing, and shipping software products and/or services

4. Building products including front end technologies or backend systems

5. Large-scale Internet service architectures (load balancing, LAMP, or CDN's)

6. Designing and developing distributed systems, storage systems, or cache and data distribution infrastructure

Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.

Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.

Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.

Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

Requires a Bachelor's degree (or foreign equivalent) in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Physics, Applied Sciences, or a related field and 60 months of progressive, post-baccalaureate experience in the job offered or in a Data Science-related occupation. Requires 60 months of progressive, post-baccalaureate experience in the following:

1. Machine learning techniques

2. Working with large data sets and network-based data, including TCP or HTTP

3. ETL (Extract, Transform, Load) processes

4. Relational databases, including SQL or PL*SQL

5. Statistical analysis using R, MATLAB, SPSS, SAS, or Stata

6. Large scale data processing infrastructures using distributed systems, including Hadoop, Hive, MapReduce, or MPI

7. Quantitative analysis techniques: clustering, regression, pattern recognition, or descriptive and inferential statistics

8. Communicating and presenting results of data analyses

Design, build, and launch data pipelines to move data across systems and build the next generation of data tools that generate business insights for a product.

Analyze user needs and software requirements to determine workability and to offer support for end users on data usage.

Design, architect, and develop software and data solutions that help product and business teams make data-driven decisions.

Rethink and influence strategy and roadmap for building efficient data solutions and scalable data warehouse plans.

Design, develop, test, and launch new data models and processes into production, and provide support.

Leverage homegrown extract, transform, and load (ETL) framework as well as off-the-shelf ETL tools, as appropriate.

Interface closely with data infrastructure, product, and engineering teams to build and extend cross platform ETL and reports generation framework.

Identify data infrastructure issues and drive to resolution.

Master’s degree (or foreign degree equivalent ) in Computer Science, Engineering, Mathematics, Physics, or related field. Requires 2 years of experience in the job offered or in a related occupation

Experience must include 24 months involving the following:

1. Data ETL (Extract, Transform, Load) design, implementation, and maintenance on a large scale

2. Programming in Python

3. Writing SQL statements

4. Analyzing large volumes of data to provide data driven insights, gaps, and inconsistencies

5. Data warehousing architecture and plans

6. Informatica, dimensional data modeling, or schema design and

7. Map Reduce or MPP system

Conduct analysis using internal and external data (e.g. customer, user, revenue, product, market, industry) to derive insights that will drive business decisions.

Develop deep understanding of the Meta ads business, analyzing business and product trends (including regional, channel and vertical performance), recognizing opportunities, and presenting recommendations to stakeholders.

Conduct deep dives through complex data analysis to extract meaningful insights for the sales and product leadership teams.

Work effectively with cross-functional teams globally, driving results in the form of data insights and building strategic partnerships.

Conceptualize, build, manage and maintain centralized tools (including dashboards) that the business and Analytics teams can use to extract data /insights for daily business management in an automated manner.

Requires a Master’s degree (or foreign equivalent) in Business Administration, Business Analytics, or a related field and 2 years of experience in the job offered or related occupation. Requires 2 years of experience in:

1. Machine learning

2. User experience (UX)

3. Research science (general category) Human-Machine Interfacing

4. Computing Architectures