Assistant Manager

EXL

. Build and operate data pipelines feeding the Entity Hub .

Posted 10/9/2026full-timeIndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in building and operating data pipelines, implementing ETL processes, and ensuring data quality through automated validation. Proficient in collaborating with stakeholders to meet data requirements and optimize data models.

Highest-signal resume keywords

Python ProgrammingPySpark DevelopmentSQL QueryingAzure Data FactoryData Engineering Experience

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DevelopmentETL ProcessesData Quality ChecksSchema DesignData Transformation LogicData ValidationAutomated Data ValidationData ModelingMetadata ManagementData Integration

Soft Skills

Problem-SolvingCommunicationAnalytical SkillsAttention to DetailTime Management

Tools & Technologies

HadoopHiveAzureDatabricksGreenplumApache OozieHueSparkData Diagram DocumentationEntity Resolution Engine

Industry Keywords

Data ScienceStatisticsComputer ScienceData QualityData RequirementsStakeholder CollaborationUAT TestingRegression TestingDistributed ComputingData Workflows

Tech Stack

Tools & technologies

ApacheAzureCloudETLGreenplumHadoopOraclePySparkPythonSparkSQL

About the role

Key responsibilities & impact

Build and operate data pipelines feeding the Entity Hub
Land six in-scope data sources into Fabric
Implement standardization and transformation logic
Maintain data quality checks and monitoring for the entity resolution engine
Work with stakeholders to understand data requirements and design, develop, and maintain complex ETL processes
Create data integration and data diagram documentation
Lead data validation, UAT, and regression testing for new data assets
Create and maintain data models, including schema design and optimization
Create and manage automated data pipelines to ensure data quality and consistency
Collaborate with data scientists, analysts, and business teams to resolve data issues and meet data requirements

Requirements

What you’ll need

Strong knowledge of Python and PySpark
Ability to write PySpark scripts for developing data workflows
Strong knowledge of SQL, Hadoop, Hive, Azure, Databricks, and Greenplum
Ability to write SQL querying metadata and tables from Oracle, Hive, Databricks, and Greenplum
Familiarity with Hadoop, Spark, and distributed computing frameworks
Ability to use Hue, run Hive SQL queries, and schedule Apache Oozie jobs
Experience communicating with stakeholders and collaborating with business teams for data testing
Strong problem-solving and troubleshooting skills
Ability to establish data quality test cases and implement automated data validation processes
Degree in Data Science, Statistics, Computer Science, or a related field, or equivalent combination of education and experience
3–7 years of experience in data engineering
Experience with Azure cloud computing, Azure Data Factory ETL processes, and Azure Databricks
Strong communication, problem-solving, analytical, time-management, multitasking, attention-to-detail, and accuracy skills