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Data Engineer (Analytics) Job Opening In Cyberjaya – Now Hiring Experian


Job description

Job Description

The role sits within our Decision Analytics, one of our four Global Business Lines.

Experian Decision Analytics helps client achieve and sustain significant growth.

We do this by enabling clients to make analytics-based customer decisions that support their strategic goals.

As experts in uniting business understanding with consumer and business information, analytics and strategy execution, we empower clients to optimise customer value and actively manage it over time.

This role therefore has clear accountability for creating measurable value within our client organisations.

What you’ll be doing

In this role, you’ll be working as an Analytics Engineer within Analytics Center of Excellence on Experian’s internal Cloud Platform.

You’ll be managing data at scale and working on key initiatives such as Data Productizations where we employ different big data technologies and back/front ends to build solutions for our clients.

More about you

  • Experience in data warehouse technologies, data modeling and ETL development
  • Experience in a high-performing, large-scale technology driven environment
  • Exposure in creating/maintaining Data pipeline (Apache Spark or similar) and workflow tools (Airflow or similar) for both Realtime and batch use cases.

    Cloud experience (Azure is preferred)
  • Basic understanding of ML, Deep learning, Wrappers and APIs
  • Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O (Mandatory)
  • Strong coding skill in SQL and (Python or Java or Scala)
  • Exposure to Database architecture using RDBMS or NoSQL: Views/Tables, Disk usage and relational diagram
  • Excellent communication, interpersonal skills, and proven project management skills.
  • Management of Hadoop cluster, with all included services, and ability to solve any ongoing issues with operating the cluster
  • Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming (Good to have)
  • Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
  • Experience with integration of data from multiple data sources
  • Knowledge of various ETL techniques and frameworks, such as Flume
  • Experience with various messaging systems, such as Kafka or RabbitMQ
  • Good understanding of Lambda Architecture, along with its advantages and drawbacks
  • Experience with Cloudera/MapR/Hortonworks
  • The role sits within our Decision Analytics, one of our four Global Business Lines.

    Experian Decision Analytics helps client achieve and sustain significant growth.

    We do this by enabling clients to make analytics-based customer decisions that support their strategic goals.

    As experts in uniting business understanding with consumer and business information, analytics and strategy execution, we empower clients to optimise customer value and actively manage it over time.

    This role therefore has clear accountability for creating measurable value within our client organisations.

    What you’ll be doing

    In this role, you’ll be working as an Analytics Engineer within Analytics Center of Excellence on Experian’s internal Cloud Platform.

    You’ll be managing data at scale and working on key initiatives such as Data Productizations where we employ different big data technologies and back/front ends to build solutions for our clients.


  • Qualifications

    More about you

  • Experience in data warehouse technologies, data modeling and ETL development
  • Experience in a high-performing, large-scale technology driven environment
  • Exposure in creating/maintaining Data pipeline (Apache Spark or similar) and workflow tools (Airflow or similar) for both Realtime and batch use cases.

    Cloud experience (Azure is preferred)
  • Basic understanding of ML, Deep learning, Wrappers and APIs
  • Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O (Mandatory)
  • Strong coding skill in SQL and (Python or Java or Scala)
  • Exposure to Database architecture using RDBMS or NoSQL: Views/Tables, Disk usage and relational diagram
  • Excellent communication, interpersonal skills, and proven project management skills.
  • Management of Hadoop cluster, with all included services, and ability to solve any ongoing issues with operating the cluster
  • Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming (Good to have)
  • Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
  • Experience with integration of data from multiple data sources
  • Knowledge of various ETL techniques and frameworks, such as Flume
  • Experience with various messaging systems, such as Kafka or RabbitMQ
  • Good understanding of Lambda Architecture, along with its advantages and drawbacks
  • Experience with Cloudera/MapR/Hortonworks

  • Additional Information

    Our uniqueness is that we celebrate yours.

    Experian's culture and people are important differentiators.

    We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering...

    the list goes on.

    Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few.

    Check out Experian Life on social or our Careers Site to understand why.

    Experian is proud to be an Equal Opportunity and Affirmative Action employer.

    Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success.

    Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age.

    If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

    Experian Careers - Creating a better tomorrow together

    Find out what its like to work for Experian by clicking here

    Required Skill Profession

    Mathematical Science Occupations


    • Job Details

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    Unlock Your Data Engineer Potential: Insight & Career Growth Guide


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    Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Data Engineer in Cyberjaya, Malaysia, highlighting market share and opportunities for professionals in Data Engineer roles.

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    Are You Looking for Data Engineer (Analytics) Job?

    Great news! is currently hiring and seeking a Data Engineer (Analytics) to join their team. Feel free to download the job details.

    Wait no longer! Are you also interested in exploring similar jobs? Search now: .

    The Work Culture

    An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Experian adheres to the cultural norms as outlined by Expertini.

    The fundamental ethical values are:

    1. Independence

    2. Loyalty

    3. Impartiapty

    4. Integrity

    5. Accountabipty

    6. Respect for human rights

    7. Obeying Malaysia laws and regulations

    What Is the Average Salary Range for Data Engineer (Analytics) Positions?

    The average salary range for a varies, but the pay scale is rated "Standard" in Cyberjaya. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

    What Are the Key Qualifications for Data Engineer (Analytics)?

    Key qualifications for Data Engineer (Analytics) typically include Mathematical Science Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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    Interview Tips for Data Engineer (Analytics) Job Success

    Experian interview tips for Data Engineer (Analytics)

    Here are some tips to help you prepare for and ace your Data Engineer (Analytics) job interview:

    Before the Interview:

    Research: Learn about the Experian's mission, values, products, and the specific job requirements and get further information about

    Other Openings

    Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

    Dress Professionally: Choose attire appropriate for the company culture.

    Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

    Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

    During the Interview:

    Be Punctual: Arrive on time to demonstrate professionalism and respect.

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    Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

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    Turn Off Phone: Avoid distractions during the interview.

    Final Thought:

    To prepare for your Data Engineer (Analytics) interview at Experian, research the company, understand the job requirements, and practice common interview questions.

    Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Experian's products or services and be prepared to discuss how you can contribute to their success.

    By following these tips, you can increase your chances of making a positive impression and landing the job!

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