E
EXL
Data Engineer
Data Engineer Snowflake
On-siteMidData Engineerposted 2mo ago
Role summaryAI-generated
This role focuses on transforming legacy systems into scalable, AI-ready data platforms while building semantic layers for business-friendly analytics. The candidate will lead pipeline optimization and collaborate with cross-functional teams to ensure data integrity and compliance in a cloud-native environment.
Skills required
Etl pipeline designSnowflakeData migrationSemantic layerCloud data architecturesData governanceData quality assuranceStakeholder collaborationSQLData lineageData pipelinesAIBusiness intelligenceData architectureData qualityStatisticsPythonSparkData warehousingDatabricksBigQueryRedshiftFeature engineeringData visualizationTableauPower BILookerCloud computingAWSAzure
About this role
This role involves building data pipelines, migrating legacy architecture to AI ready data & semantic layer, collaborating with stakeholders, and optimizing data workflows to support advanced analytics and business intelligence initiatives.
Responsibilities
Key Responsibilities
- Design, build, and maintain robust, scalable, and reliable data pipelines to support analytics, reporting, and AI/ML use cases
- Lead the migration of legacy data architectures to modern, cloud‑based, AI‑ready data platforms
- Develop and implement semantic layers to enable consistent, business‑friendly access to data for analytics and BI tools
- Collaborate closely with business stakeholders, data scientists, analysts, and product teams to understand data requirements and translate them into technical solutions
- Ensure data quality, integrity, security, and compliance through validation, monitoring, and governance best practices
- Document data architectures, pipelines, and best practices to support knowledge sharing and long‑term maintainability
Qualifications
- Bachelors / Master’s degree in Economics, Statistics, Engineering or a related quantitative field from a top-tier university
- Advanced Python & Pyspark: 2+ years of hands-on experience with performance tuning and complex query optimization
- Hands‑on experience with modern data architectures such as data lakes, lakehouses, and data warehouses such as Snowflake, Databricks, BigQuery, or Redshift
- Snowflake certification (SnowPro Core required; SnowPro Advanced preferred)
- Excellent communication skills, with the ability to explain technical concepts to non‑technical audiences
Desirable Skills (Good-to-Have)
- Experience supporting AI/ML pipelines and feature engineering
- Working knowledge of data visualization software such as Tableau, Power BI and Looker
- Hands-on experience with cloud platforms: AWS, Azure, or GCP.
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