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EXL
EXL
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EXL is a business consulting and services company that helps organizations use data, analytics, and technology to improve operations and make better decisions. Its work includes operations management, decision analytics, and digital transformation, with experience supporting clients in healthcare, insurance, finance, and logistics. EXL combines data science with practical business expertise to develop solutions tailored to each organization’s goals, operating model, and industry context.
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Mid-Senior Data Engineer - Hybrid in Noida

Join EXL as a mid-senior Data Engineer in hybrid Noida, developing scalable Databricks and Snowflake platforms. Build ETL/ELT pipelines, data models, and cloud analytics solutions with Python, SQL, and Spark.

INIndiaHybridFull-timeMiddleSeniorEnglish RequiredData Engineer
ApacheAWSAzureCloudETLGoogle Cloud PlatformPythonSparkSQL

Description

  • Partner with senior data engineers and architects to develop, optimize, and support scalable data pipelines and workflows.
  • Create ETL/ELT processes with Databricks, Spark, Python, and SQL.
  • Design and implement ingestion frameworks for structured and unstructured data.
  • Develop and maintain Snowflake data models, data marts, and analytical datasets.
  • Monitor pipeline operations and improve performance, reliability, and scalability.
  • Work with stakeholders, analysts, and data scientists to clarify requirements and deliver data solutions.
  • Contribute to architecture discussions, proof-of-concepts, and process improvement efforts.
  • Record data flows, technical designs, and implementation details for operational support and knowledge sharing.
  • Apply data quality, security, and governance standards across data platforms.

Requirements

  • Bachelor’s or master’s degree in computer science, information technology, engineering, data science, or a related technical discipline.
  • Solid knowledge of SQL and core database concepts.
  • Proficiency in Python or a comparable programming language.
  • Understanding of data warehousing, ETL/ELT workflows, and data modeling.
  • Exposure to Databricks, Apache Spark, Snowflake, or cloud data platforms through projects, internships, certifications, hackathons, or personal work.
  • Basic familiarity with Azure, AWS, or Google Cloud Platform is advantageous.
  • Strong analytical and problem-solving abilities, with enthusiasm for learning modern data engineering technologies.
  • Effective communication and collaboration skills.

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