Data Engineer (PySpark)
Capgemini
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired bya collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizationsunlock the value of technology and build a more sustainable, more inclusive world. Responsibilities Monitor and control all phases of development process and analysis design construction testing and implementation as well as provide user and operational support on applications to business users Utilize indepth specialty knowledge of applications development to analyze complex problemsissues provide evaluation of business process system process and industry standards and make evaluative judgement Recommend and develop security measures in post implementation analysis of business usage to ensure successful system design and functionality Consult with usersclients and other technology groups on issues recommend advanced programming solutions and install and assist customer exposure systems Ensure essential procedures are followed and help define operating standards and processes Serve as advisor or coach to new or lower level analysts Has the ability to operate with a limited level of direct supervision Can exercise independence of judgement and autonomy Acts as SME to senior stakeholders and or other team members Qualifications 58 years of relevant experience Experience in systems analysis and programming of software applications Experience in managing and implementing successful projects Working knowledge of consultingproject management techniquesmethods Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements Education Bachelors degreeUniversity degree or equivalent experience This job description provides a highlevel review of the types of work performed Other jobrelated duties may be assigned as required Indepth understanding of HDFS architecture data storage and fault tolerance mechanisms Experience with HDFS commands and administration Solid understanding of YARN resource management and job scheduling Fundamental understanding of MapReduce programming paradigm even if primary development is in SparkFlinkKnowledge of Zookeeper for distributed coordination services StrongproficiencyinSpark Core Spark SQL Spark Streaming and SparkGraphXbeneficialExpertlevel programming skills inPython and Pyspark specifically for developing Spark applications Experience with Spark performance optimization techniques eg caching partitioning shuffle optimizations memory management Experience withPySparkfor data processingFamiliarity with data manipulation libraries Pandas NumPyScripting for automation and data orchestration Complex query writing subqueries window functions and performance tuningHBase for realtime access to large datasets within HadoopCassandra MongoDB or similarFamiliarity with RDBMS concepts and SQL for data integration Understanding of dimensional modeling fact and dimension tables starsnowflake schemas The base compensation range for this role in the posted location is: 80,000 - 90,000 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. #J-18808-Ljbffr Capgemini
$60k - $135k
Job Description Role: Data Engineer - PySpark Location: Irving, TX (3 Days onsite/week) Key Responsibilities Strong programming skills in PySpark in a BigData environment with exceptional hands-on capabilities Familiarity with big data processing tools and techniques. Experience...SuggestedMinimum wageLocal area3 days per week- Capgemini in the United States is seeking a data engineer to design, build and optimize large-scale data pipelines using Hadoop, Spark, PySpark, and the HDFS ecosystem. You will drive performance tuning, data integration and analytics for business stakeholders. Ideal candidates...Suggested
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$50 - $60 per hour
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$60k - $110k
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