[Remote] Lead Data Engineer

Note: The job is a remote job and is open to candidates in USA. EXL is seeking a Senior Data Engineer to join its Data & Analytics practice and support strategic client engagements. The role designs, builds, and manages scalable cloud-based data platforms, develops modern data engineering practices, and leads teams delivering data solutions for analytics, reporting, AI, and operational use cases.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data products supporting analytics, reporting, AI, and operational use cases
• Build and optimize ETL/ELT frameworks for large-scale data ingestion, transformation, validation, and consumption
• Develop and manage cloud-native data platforms leveraging Snowflake, AWS, Apache Airflow and modern data architectures
• Create scalable data models, data marts, semantic layers, and curated datasets that support enterprise analytics initiatives
• Optimize SQL workloads, transformation logic, and query performance to improve scalability and cost efficiency
• Establish reusable engineering frameworks, accelerators, and best practices to improve delivery consistency across projects
• Ensure high standards of data quality, reliability, governance, and observability throughout the data lifecycle
• Develop and maintain Snowflake-based data ecosystems, leveraging advanced features for performance optimization and data sharing
• Build and orchestrate data workflows using Airflow and other workflow scheduling platforms
• Collaborate directly with client stakeholders to gather requirements, define roadmaps, and develop scalable technical solutions
• Present solution designs, technical recommendations, and project updates to both technical and business audiences
• Prepare and maintain comprehensive project documentation, technical specifications, architecture diagrams, and operational runbooks

Skills

• 4+ years of experience in Data Engineering, Big Data Engineering, or Cloud Data Platform development
• Bachelor's or Master's degree in Computer Science, Engineering, Analytics, Mathematics, Information Systems, or related disciplines
• Strong hands-on expertise in SQL, Python, and PySpark
• Extensive experience working with Snowflake, Databricks, or similar cloud-native data platforms
• Proven experience building and supporting large-scale ETL/ELT data pipelines
• Strong understanding of data warehousing concepts, dimensional modeling, and modern Lakehouse architectures
• Experience implementing Medallion Architecture and enterprise-grade data modeling practices
• Hands-on experience with workflow orchestration tools such as Apache Airflow or equivalent scheduling frameworks
• Experience working with cloud ecosystems including AWS, Azure, or GCP
• Strong knowledge of performance tuning, optimization, monitoring, and operational support for data platforms
• Demonstrated experience leading engineering teams and coordinating with client and internal stakeholders
• Excellent analytical, problem-solving, communication, and stakeholder management skills
• Ability to work independently and lead complex initiatives in fast-paced consulting environments
• Experience with streaming and real-time data processing frameworks
• Familiarity with DataOps, CI/CD, Infrastructure as Code, and DevOps practices
• Experience with data governance, data quality frameworks, and metadata management
• Exposure to AI/ML data pipelines and feature engineering workflows
• Experience with visualization tools such as Tableau, Power BI, or Looker
• Hands-on experience with Big Data technologies including Spark, Hadoop, Hive, HBase, Kafka, or related platforms
• Consulting or client-facing delivery experience in enterprise-scale environments

Company Overview

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