Support Engineer – Data & Cloud Platforms

Job Role: Support Engineer – Data & Cloud Platforms

About the Role

Key Responsibilities

• Provide Tier 3 production support for complex applications, data platforms, pipelines, and enterprise solutions.
• Independently investigate and resolve complex application, data, platform, and performance issues using logs, monitoring, code analysis, and technical research.
• Perform Root Cause Analysis (RCA) and implement permanent fixes, configuration changes, and code-level enhancements.
• Troubleshoot and optimize Databricks, Snowflake, Cloudera, Spark, Dagster, and dbt environments and data pipelines.
• Collaborate with DevOps, Product Engineering, Data Engineering, and Support teams to resolve critical incidents.
• Support major incident management, on-call escalations, and SLA-driven production environments.
• Develop proactive monitoring and preventive solutions to reduce recurring incidents.
• Support deployment and implementation of enterprise solutions while ensuring adherence to engineering and platform standards.
• Troubleshoot integrations across cloud, data, application, infrastructure, and security ecosystems.

Must-Have Skills & Experience

• 5+ years of experience in enterprise production/support engineering roles.
• Strong hands-on experience with Databricks, including troubleshooting, performance tuning, and pipeline orchestration.
• Hands-on experience with Cloudera/Hadoop, including Spark, Ranger, Hue, YARN, and performance optimization.
• Strong Python development and production troubleshooting experience.
• 3+ years of experience supporting Dagster + dbt integrations and data orchestration pipelines.
• Strong experience with SQL, PySpark, Snowpark, Spark, and data processing technologies.
• Experience with Node.js, MongoDB, and enterprise software development/support.
• Proficiency with Git/GitHub and Git-based development workflows.
• Experience working in high-pressure, SLA-driven enterprise production environments.
• 3+ years of experience across AWS and/or GCP cloud environments.
• Hands-on experience with Infrastructure as Code (IaC) and deployment automation.
• Experience with Citrix environments.
• Strong troubleshooting, analytical, communication, and incident-management skills.

Good to Have

• Experience with Data Lake architecture, ETL/ELT, schema validation, and data integrity.
• Experience with Tableau, Unica, Jenkins, Google Pub/Sub, or similar enterprise platforms.
• Experience building or supporting automated testing frameworks.
• Hands-on experience with Databricks Unity Catalog, security, and governance.
• Experience with IAM, SSO, Okta, and enterprise identity platforms.
• Experience with Kubernetes, Docker, Terraform, and CI/CD environments.
• Experience with production logging and observability tools such as ServiceNow, Observe, Coralogix, and OpenSearch.
• Exposure to Scala, Perl, Oracle, React, Spring Framework, or similar technologies.
• Experience supporting cloud data platforms and distributed data ecosystems.

Certifications

• Databricks Certified Data Analyst or
• Snowflake SnowPro Advanced: Data Analyst

• AWS Certified Data Engineer

What Will Make You Successful

• Strong ability to independently troubleshoot ambiguous and complex production issues.
• Ability to analyze logs, trace failures, understand custom code, and identify root causes with minimal supervision.
• Strong ownership of production incidents from identification through resolution and prevention.
• Ability to work effectively with cross-functional engineering and client teams.
• Strong focus on system reliability, performance, automation, and continuous improvement.

Why Join Anblicks?