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Data Engineer

Capgemini is looking for a skilled Data Engineer to join our dynamic team.

In this role, you will be responsible for designing, implementing, and maintaining data pipelines and architectures, ensuring efficient data processing and storage. You will collaborate closely with data scientists and analysts to support data analysis and reporting needs, making sure data quality and integrity are upheld throughout the data lifecycle. Your role will be pivotal in driving data initiatives and optimizing data workflows, enabling better decision-making through data-driven insights.

As part of a leading global consulting firm, Capgemini provides opportunities to work on diverse projects and leverage cutting-edge technologies in the data engineering space.

Role Description:

  • Consults independently, works iteratively, and is viewed as an expert on data projects of a complex nature.
  • Ability to understand design requirement and existing business processes to lead in the design, development, and implementation of data products in partnership with business partners and data scientists.
  • Produces complex data building blocks, data models, and data flows working with business partners and data scientists within personal lines and distribution domains to deliver requests such as dimensional data models, standard and ad hoc reporting, data feeds, dashboard reporting, ad hoc analysis, data profiling etc.
  • Designs and manages highly complex projects while handling multiple complex cross-functional projects.
  • Preps/cleanses data to optimize for downstream reporting using Farmers standards.
  • Functions as an expert in serving as a SME for appropriate data sources and for how best to operationalize solutions working closely with business partners and data scientists.
  • Acts as a conduit between business and IT teams for all aspects of the work.
  • Create Dimensional Data Models, STTM’s and other technical documents for offshore developers and oversee technical delivery of projects by conducting code reviews, documentation reviews etc.
  • Design, develop and maintain scalable and efficient data pipelines using cloud services such as AWS Glue, Lambda, Airflow, Event Bridge or equivalent/ related. Performs other duties as assigned.

Total Work Experience: Minimum Required: 4-6 years

English Proficiency: Intermediate

Required Education: Bachelor's Degree in Computer Science, Information Technology, or related field

Additional Preferred Branch(es) of Study


Practical knowledge of SQL, Dimensional modeling, Query tuning, ETL orchestration, PowerBI, Python, preferred.

• Hands-on experience with multiple cloud platforms including AWS, Google, and Azure preferred with exposure to services like S3, IAM roles, EC2 or equivalent

• Hand on experience with developing on SSIS and SSAS, preferred.

• Hands-on experience of SQL, Query tuning, AWS Glue, Python, PySpark preferred.

• Hands-on experience with multiple cloud platforms including AWS, and Azure.

• Hands-on experience with RESTful APIs and methods, status codes, request response cycles

• Hands-on experience with data serialization formats and proficiency in working with data formats such as JSON, PARQUET, XML

• Hands-on experience in CI/CD framework to enable automated deployments.

• Solid ability to consume APIS from various sources, integrate into code, extract relevant data and handle different response formats.

• Understanding of API security best practices, including authentication, authorization and data encryption

• Ability to understand API documentation (e.g. Swagger, OpenApi).

• Knowledge of data quality and data governance processes

• Possesses strong technical aptitude, preferred.

• Strong verbal communication and listening skills, preferred.

• Extensive experience interacting with senior leadership stakeholders around the topics of data access, quality, appropriate use, metric definitions and standardization, preferred.

• Effectively coaches junior members and delivers constructive feedback

Competitive compensation and benefits package:

  1. Competitive salary and performance-based bonuses
  2. Comprehensive benefits package
  3. Career development and training opportunities
  4. Flexible work arrangements (remote and/or office-based)
  5. Dynamic and inclusive work culture within a globally renowned group
  6. Private Health Insurance
  7. Pension Plan
  8. Paid Time Off
  9. Training & Development

Note: Benefits differ based on employee level.

About Capgemini

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 340,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group €22.5 billion in revenues in 2023.

https://www.capgemini.com/us-en/about-us/who-we-are/

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Average salary estimate

$100000 / YEARLY (est.)
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$80000K
$120000K

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What You Should Know About Data Engineer, Capgemini

Capgemini is on the lookout for a talented Data Engineer to join our innovative team! In this exciting role, you will design, implement, and maintain data pipelines and architectures that ensure smooth and efficient data processing and storage. Collaborating closely with data scientists and analysts, you'll support their data analysis and reporting needs, while prioritizing data quality and integrity throughout the entire data lifecycle. Your expertise will play a vital role in enhancing our data initiatives and streamlining workflows, ultimately empowering teams with data-driven insights. At Capgemini, a leader in global consulting, you’ll have the chance to work on diverse projects and utilize cutting-edge technologies within the data engineering realm. You'll take charge of crafting complex data models and building data flows, collaborating with business partners to fulfill reporting and analysis requests. Managing multiple cross-functional projects and leveraging cloud services like AWS Glue and Lambda will be part of your daily routine. With a minimum of 4-6 years of relevant experience and a Bachelor's degree in a related field, this position calls for individuals who are not only proficient in SQL and ETL orchestration but also comfortable with cloud platforms like AWS and Azure. With a competitive salary and comprehensive benefits, including training and development opportunities, Capgemini truly invests in your future.

Frequently Asked Questions (FAQs) for Data Engineer Role at Capgemini
What are the main responsibilities of a Data Engineer at Capgemini?

As a Data Engineer at Capgemini, your primary responsibilities include designing, implementing, and maintaining data pipelines and architectures. You will work closely with data scientists and analysts to support their data analysis needs while ensuring data quality and integrity. Your role will also involve creating complex data models and overseeing cross-functional projects to optimize data workflows.

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What qualifications are required for the Data Engineer position at Capgemini?

Candidates for the Data Engineer role at Capgemini should possess a Bachelor's degree in Computer Science, Information Technology, or a related field, along with 4-6 years of relevant work experience. Preferred qualifications include practical knowledge of SQL, ETL orchestration, and familiarity with cloud platforms like AWS, Google, or Azure.

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What technologies should a successful Data Engineer at Capgemini be familiar with?

A successful Data Engineer at Capgemini should be well-versed in technologies such as SQL, Python, AWS Glue, and data serialization formats like JSON and PARQUET. Familiarity with cloud services, RESTful APIs, and CI/CD frameworks for automated deployments is also highly beneficial.

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How can a Data Engineer at Capgemini contribute to data quality and governance?

In your role as a Data Engineer at Capgemini, you will contribute to data quality and governance by ensuring that data pipelines uphold strict quality standards and by developing processes for data profiling and cleansing. Moreover, your expertise will be instrumental in communicating data access and quality topics to stakeholders.

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What are the career development opportunities available for Data Engineers at Capgemini?

Capgemini offers numerous career development opportunities for Data Engineers, including comprehensive training programs and mentorship arrangements. Our dynamic work environment encourages continuous learning and the chance to work on cutting-edge projects that further enhance your technical skills.

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Common Interview Questions for Data Engineer
Can you describe your experience with ETL processes as a Data Engineer?

When discussing your experience with ETL processes, focus on specific tools you have used, such as AWS Glue or SSIS. Detail how you have designed and maintained ETL workflows, any challenges you faced, and how you ensured data quality throughout.

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How do you optimize data pipelines for performance?

Explain your approach to optimizing data pipelines by mentioning techniques like query tuning, data partitioning, and using efficient data formats such as PARQUET. Describe any specific examples where your optimizations led to improved performance.

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What strategies do you use for data quality assurance?

Discuss your strategies for data quality assurance such as implementing validation checks during the data pipeline stages, conducting regular data profiling, and collaborating with data stakeholders to define quality metrics.

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How familiar are you with cloud services related to data engineering?

Mention your hands-on experience with cloud services such as AWS, Google Cloud Platform, or Azure. Highlight any specific services you used, such as S3 or EC2, and how you've leveraged these to create efficient data pipelines.

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Can you share an example of a complex data model you've built?

Prepare for this question by outlining a detailed example of a complex data model you've developed, explaining its purpose, the challenges you faced, and how it impacted business decisions. Use this as an opportunity to showcase your modeling skills.

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How do you approach collaboration with data scientists and business stakeholders?

Emphasize your communication and collaborative skills. Describe how you successfully collaborated with data scientists and business stakeholders in the past to define requirements, clarify data needs, and iterate on data solutions until they met their expectations.

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What role do APIs play in your data engineering work?

Illustrate your understanding of APIs by discussing how you've utilized RESTful services to consume and integrate data from various sources into your data pipelines. Mention any challenges you faced with API authentication or handling different data formats.

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How do you ensure scalability in your data solutions?

Describe how you design and implement scalable data architectures that can handle increasing amounts of data and user requests effectively. Discuss the importance of using cloud-based solutions that offer scaling capabilities, such as AWS Lambda.

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What tools or technologies do you use for data version control?

Talk about the data version control tools you use, such as Git or similar, to manage changes in your data engineering projects. Explain how version control is crucial for collaboration and maintaining the integrity of your data solutions.

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What do you consider when designing data governance policies?

When designing data governance policies, discuss the factors you consider, such as data security, privacy regulations, and the need for clear definitions around data access, ownership, and usage rights to ensure compliance and accountability.

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DATE POSTED
April 12, 2025

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