Senior ETL/Cloud Data Engineer

Job Title: Senior ETL / Cloud Data Engineer

Experience: 11+ Years

About the Role

We are seeking a highly experienced Senior ETL/Cloud Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms. The ideal candidate has a strong background in ETL development, cloud data architecture, and large-scale data processing, with a proven ability to lead technical initiatives and mentor junior engineers.

Key Responsibilities

• Design, develop, and maintain robust, scalable ETL/ELT pipelines to support batch and real-time data processing needs
• Architect and implement cloud-based data solutions on AWS/Azure/Google Cloud Platform, including data lakes, data warehouses, and lakehouse platforms
• Lead the migration of legacy on-premise ETL systems to modern cloud-native architectures
• Build and optimize data ingestion frameworks from diverse sources (databases, APIs, streaming platforms, flat files)
• Design and maintain data models, schemas, and data warehousing solutions (Star/Snowflake schema, dimensional modeling)
• Ensure data quality, integrity, and governance across pipelines through validation, monitoring, and automated testing
• Collaborate with data architects, analysts, data scientists, and business stakeholders to understand requirements and deliver solutions
• Optimize pipeline performance, cost efficiency, and scalability of cloud data infrastructure
• Implement CI/CD pipelines for data engineering workflows using DevOps best practices
• Establish and enforce data engineering best practices, coding standards, and documentation
• Troubleshoot and resolve complex data pipeline issues, ensuring high availability and reliability
• Mentor junior and mid-level data engineers; conduct code reviews and provide technical guidance
• Stay current with emerging cloud technologies, tools, and industry trends

Required Skills & Qualifications

• 11+ years of overall experience in data engineering, with significant hands-on ETL and cloud experience
• Strong expertise in ETL tools such as Informatica, Talend, SSIS, DataStage, or similar
• Deep hands-on experience with at least one major cloud platform: AWS (Glue, Redshift, S3, Lambda, EMR), Azure (Data Factory, Synapse, Databricks), or Google Cloud Platform (Dataflow, BigQuery, Dataproc)
• Proficiency in SQL and at least one programming language (Python, Scala, or Java)
• Experience with big data technologies: Spark, Hadoop, Kafka, Hive
• Strong understanding of data warehousing concepts, dimensional modeling, and data architecture principles
• Experience with orchestration tools (Apache Airflow, Control-M, AWS Step Functions, etc.)
• Familiarity with CI/CD tools (Jenkins, Git, Azure DevOps) and Infrastructure as Code (Terraform, CloudFormation)
• Solid understanding of database systems (both relational and NoSQL — Oracle, SQL Server, PostgreSQL, MongoDB, Cassandra)
• Experience with data governance, security, and compliance practices
• Excellent problem-solving skills and ability to work in a fast-paced, evolving environment
• Strong communication skills with experience presenting to technical and non-technical stakeholders

Preferred Qualifications

• Cloud certifications (AWS Certified Data Analytics, Azure Data Engineer Associate, Google Cloud Platform Professional Data Engineer)
• Experience with real-time streaming architectures (Kafka, Kinesis, Event Hubs)
• Exposure to containerization and orchestration (Docker, Kubernetes)
• Experience in a regulated industry (finance, healthcare, insurance) is a plus
• Prior experience leading a team or serving as a technical lead