Data Engineer

Reposted 10 Days Ago
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Gurugram, Haryana, IND
Hybrid
Senior level
Information Technology • Database • Consulting
The Role
Design, develop, and maintain ETL pipelines, data models, and data assets. Collaborate with stakeholders for requirements, lead data validation/UAT/regression testing, create integration documentation, and implement automated data quality and validation processes.
Summary Generated by Built In

Data Engineer (DE) Consultant is responsible for designing, developing, and maintaining data assets and data related products by liaising with multiple stakeholders.

Responsibilities

Responsibilities:

  • Work with stakeholders to understand the data requirements to design, develop, and maintain complex ETL processes.
  • Create the data integration and data diagram documentation. 
  • Lead the data validation, UAT and regression test for new data asset creation.
  • Create and maintain data models, including schema design and optimization.
  • Create and manage data pipelines that automate the flow of data, ensuring data quality and consistency.
Qualifications

Qualifications and Skills:

  • Strong knowledge on Python and Pyspark 
    • Expectation is to have ability to write Pyspark scripts for developing data workflows. 
  • Strong knowledge on SQL, Hadoop, Hive, Azure, Databricks and Greenplum 
    • Expectation is to write SQL to query metadata and tables from different data management system such as, Oracle, Hive, Databricks and Greenplum.
    • Familiarity with big data technologies like Hadoop, Spark, and distributed computing frameworks.
    • Expectation is to use Hue and run Hive SQL queries, schedule Apache Oozie jobs to automate the data workflows.
  • Good working experience of communicating with the stakeholders and collaborate effectively with the business team for data testing.
    • Expectation is to have strong problem-solving and troubleshooting skills.
    • Expectation is to establish comprehensive data quality test cases, procedures and implement automated data validation processes.
  • Degree in Data Science, Statistics, Computer Science or other related fields or an equivalent combination of education and experience.
  • 5-7 years of experience in Data Engineer.
  • Proficiency in programming languages commonly used in data engineering, such as Python, Pyspark, SQL.
  • Experience in Azure cloud computing platform, such as developing ETL processes using Azure Data Factory, big data processing and analytics with Azure Databricks.
  • Strong communication, problem solving and analytical skills with the ability to do time management and multi-tasking with attention to detail and accuracy.

Skills Required

  • 5-7 years of experience in Data Engineering
  • Degree in Data Science, Statistics, Computer Science or related field (or equivalent experience)
  • Strong knowledge of Python and Pyspark with ability to write Pyspark scripts for data workflows
  • Proficiency in SQL and ability to query metadata and tables from Oracle, Hive, Databricks and Greenplum
  • Experience with Hadoop, Spark and distributed computing frameworks
  • Experience with Azure cloud platform, including Azure Data Factory and Azure Databricks for ETL and big data processing
  • Experience working with Databricks and Greenplum
  • Experience using Hue and running Hive SQL queries; scheduling Apache Oozie jobs to automate workflows
  • Ability to create and maintain data models, schema design and optimization
  • Experience creating data integration and data diagram documentation
  • Experience leading data validation, UAT and regression testing and implementing automated data validation processes
  • Strong communication, problem solving, analytical skills, time management and multitasking ability
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The Company
HQ: New York, NY
30,246 Employees
Year Founded: 1999

What We Do

Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.

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