Your key responsibilities

• Lead the design, monitoring, and optimization of AWS-based data pipelines using services like AWS Glue, EMR, Lambda, and Amazon S3.
• Oversee and enhance complex ETL workflows involving IICS (Informatica Intelligent Cloud Services), Databricks, and native AWS tools.
• Collaborate with data engineering and analytics teams to streamline ingestion into Amazon Redshift and lead data validation strategies.
• Manage job orchestration using Apache Airflow, AWS Data Pipeline, or equivalent tools, ensuring SLA adherence.
• Guide SQL query optimization across Redshift and other AWS databases for analytics and operational use cases.
• Perform root cause analysis of critical failures, mentor junior staff on best practices, and implement preventive measures.
• Lead deployment activities through robust CI/CD pipelines, applying DevOps principles and automation.
• Own the creation and governance of SOPs, runbooks, and technical documentation for data operations.
• Partner with vendors, security, and infrastructure teams to ensure compliance, scalability, and cost-effective architecture.

Skills and attributes for success

• Expertise in AWS data services and ability to lead architectural discussions.
• Analytical thinker with the ability to design and optimize end-to-end data workflows.
• Excellent debugging and incident resolution skills in large-scale data environments.
• Strong leadership and mentoring capabilities, with clear communication across business and technical teams.
• A growth mindset with a passion for building reliable, scalable data systems.
• Proven ability to manage priorities and navigate ambiguity in a fast-paced environment.

To qualify for the role, you must have

• 5–8 years of experience in DataOps, Data Engineering, or related roles.
• Strong hands-on expertise in Databricks.
• Deep understanding of ETL pipelines and modern data integration patterns.
• Proven experience with Amazon S3, EMR, Glue, Lambda, and Amazon Redshift in production environments.
• Experience in Airflow or AWS Data Pipeline for orchestration and scheduling.
• Advanced knowledge of IICS or similar ETL tools for data transformation and automation.
• SQL skills with emphasis on performance tuning, complex joins, and window functions.