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EXL

Data Engineer

EXL

Data Engineer responsible for designing and optimizing data pipelines and data models. Collaborating with senior engineers and data scientists for scalable cloud-based solutions.

Posted 7/17/2026full-timeNoida • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and optimizing scalable data pipelines using ETL/ELT processes with tools like Databricks, Spark, and SQL. Strong analytical skills and collaboration with stakeholders to ensure data quality and governance.

Highest-signal resume keywords
ETL/ELT ProcessesDatabricksApache SparkSQLData Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
PythonData Warehousing ConceptsData Ingestion FrameworksData Pipeline Performance MonitoringData Quality Standards
Soft Skills
Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaboration Skills
Tools & Technologies
SnowflakeAzureAWSGCP
Industry Keywords
Data GovernanceData SecurityData ArchitectureData Mart

Tech Stack

Tools & technologies
ApacheAWSAzureCloudETLGoogle Cloud PlatformPythonSparkSQL

About the role

Key responsibilities & impact
  • Work with senior data engineers and architects to build, optimize, and maintain scalable data pipelines and workflows.
  • Develop ETL/ELT processes using Databricks, Spark, Python, and SQL.
  • Design and implement data ingestion frameworks for structured and unstructured data sources.
  • Build and maintain data models, data marts, and analytical datasets in Snowflake.
  • Monitor, troubleshoot, and improve data pipeline performance, reliability, and scalability.
  • Collaborate with business stakeholders, analysts, and data scientists to understand data requirements and deliver solutions.
  • Participate in architecture discussions, proof-of-concepts, and process improvement initiatives.
  • Document data flows, technical designs, and implementation details to support operational excellence and knowledge sharing.
  • Ensure adherence to data quality, security, and governance standards across data platforms.

Requirements

What you’ll need
  • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field.
  • Strong foundation in SQL and database concepts.
  • Good programming skills in Python or a similar language.
  • Understanding of data warehousing concepts, ETL/ELT processes, and data modeling.
  • Familiarity with Databricks, Apache Spark, Snowflake, or cloud data platforms through academic projects, internships, certifications, hackathons, or personal projects.
  • Basic knowledge of cloud platforms such as Azure, AWS, or GCP is a plus.
  • Strong analytical and problem-solving skills with a passion for learning modern data engineering technologies.
  • Excellent communication and collaboration skills.

Benefits

Comp & perks
  • Hands-on learning environment
  • Exposure to cloud-based data platforms
  • Develop expertise in modern data engineering technologies