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Job Description
We are seeking a skilled and experienced Data Engineering Trainer / Consultant to join our dynamic team. The ideal candidate will be responsible for delivering comprehensive training sessions on Data Engineering technologies, catering to both internal and external stakeholders. In addition, the candidate will play a crucial role in understanding client requirements, creating effective roadmaps, and supporting internal teams such as sales and marketing in generating relevant collaterals and data points related to Data Engineering.
Key Responsibilities:
1. Training:
- Design and deliver engaging and comprehensive training sessions on various Data Engineering technologies, tools, and best practices.
- Create training materials, presentations, and hands-on exercises to facilitate effective learning experiences for both technical and non-technical audiences.
- Adapt training content to cater to the needs of different audiences, including internal teams and external clients.
2. Client Engagement:
- Collaborate with clients to understand their Data Engineering requirements and challenges.
- Analyze client needs and contribute to the development of customized roadmaps and solutions that align with their business goals.
- Provide expert guidance and recommendations to clients regarding Data Engineering strategies and implementation.
3. Collateral and Data Point Creation:
- Work closely with the sales and marketing teams to create compelling collaterals, presentations, case studies, and data-driven content related to Data Engineering.
- Develop data points and visualizations that effectively communicate the value of Data Engineering solutions to prospective clients.
4. Continuous Learning:
- Stay up to date with the latest trends, tools, and advancements in Data Engineering and related fields.
- Continuously enhance personal expertise and share knowledge with the team and stakeholders.
5. Team Collaboration:
- Collaborate with cross-functional teams, including sales, marketing, and technical departments, to align training and consulting efforts with overall business objectives.
- Provide technical insights and expertise to internal teams, contributing to effective client communication and project execution.
6. Documentation:
- Maintain accurate documentation of training materials, client interactions, and project details.
- Document best practices and lessons learned from client engagements to support future projects and knowledge sharing.
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Qualifications:
- Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field.
- Proven experience as a Data Engineer, Data Analyst, or related role, with a deep understanding of Data Engineering concepts, tools, and technologies.
- Strong communication and presentation skills, with the ability to effectively convey technical concepts to both technical and non-technical audiences.
- Prior experience in delivering training sessions and workshops, preferably in a corporate or consulting environment.
- Proficiency in popular Data Engineering tools and frameworks (e.g., Apache Spark, Hadoop, SQL, ETL pipelines).
- Ability to analyze client requirements, develop strategic roadmaps, and propose effective solutions.
- Experience collaborating with sales and marketing teams to create impactful collaterals and data-driven content.
- Strong problem-solving skills and the ability to adapt to different client scenarios.
- Excellent organizational skills and attention to detail.
- Continuous learner who stays updated with industry trends and advancements.
- Relevant certifications in Data Engineering or related fields are a plus.
Application Process:
To apply, please share your profile to careers@lera.us.
Skills
ConsultantConsultingData AnalystData ScienceEtlImplementationKnowledge SharingPresentationSqlTrainingIf an employer asks you to pay any kind of fee, please notify us immediately. Jobaaj does not charge any fee from the applicants and we do not allow other companies also to do so.
About Company
Important dates & deadlines?
Application Deadline
30 Sep 23, 06:11 PM IST
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