Data Engineer 1

Overview

Data Engineer 1 is a developing-level database infrastructure and data engineering role supporting multi-technology database platforms across project delivery and day-to-day operations. The role contributes to database infrastructure design, provisioning, configuration, monitoring, troubleshooting, maintenance, and documentation under the guidance of senior engineers and platform specialists.

What you'll do

• Support database infrastructure projects from requirements and design through build, testing, go-live, handover, and decommissioning.
• Help gather workload, capacity, availability, recovery, security, networking, and support requirements.
• Assist with provisioning and configuration of Elasticsearch, AWS Managed Databases, MongoDB, MySQL, PostgreSQL, Redis, and related services.
• Follow approved patterns for naming, tagging, sizing, topology, access, encryption, backups, monitoring, and alerting.
• Support migration, upgrade, patching, scaling, replication, and cutover activities with appropriate supervision.
• Perform validation and testing before production release, including connectivity, functionality, performance, backup, restore, and failover checks.
• Maintain project documentation, architecture details, implementation notes, known issues, and operational handover information.
• Identify gaps in monitoring, alerting, runbooks, access, backup, recovery, and support readiness before go-live.
• Perform routine database and cluster health checks across supported technologies and environments.
• Review dashboards, alerts, logs, capacity indicators, backup status, replication health, and service events.
• Participate in incident triage, troubleshooting, escalation, incident bridges, and post-incident follow-up.
• Use approved runbooks and change processes for configuration changes, maintenance, patching, scaling, failover, and recovery activities.
• Start with read-only investigation, verify the target environment, and seek peer confirmation before production-impacting actions.
• Help diagnose connectivity failures, high latency, slow queries, lock contention, replication lag, cluster imbalance, shard or partition pressure, cache eviction, and storage capacity risk.
• Capture timelines, evidence, hypotheses, actions, validation results, and outstanding follow-ups in the appropriate support record.
• Update operational documentation when procedures, platform behavior, ownership, dashboards, or escalation paths change.
• Escalate early when customer impact is high, an issue is outside the documented procedure, or a proposed action has material risk.
• Collaborate with team members to co-develop solutions and solve infrastructure and database problems.
• Connect with peers across environments and technology teams to learn, coordinate, and resolve issues.
• Participate in code reviews, design discussions, incident reviews, and project ceremonies.
• Build deeper expertise in one or more database technologies while maintaining awareness of the broader platform landscape.
• Apply software design principles, data structures, algorithms, and computer science fundamentals to engineering and automation work.
• Execute tasks and provide data or technical inputs that support solutions across people, process, technology, and platform architecture.
• Report work status, risks, dependencies, and blockers clearly and on time.
• Ask thoughtful and challenging questions and respectfully challenge assumptions, authority, or the status quo when there is a clear technical or operational rationale.

What you'll need

• Ability to work under the guidance of senior engineers and platform specialists.
• Ability to follow established operational practices and seek guidance when needed.
• Understanding of system and technology integration across databases, applications, networks, cloud services, monitoring, and security controls.
• Familiarity with highly available, distributed systems used for data storage, retrieval, caching, search, extraction, ingestion, and processing.
• Ability to seek support from subject matter experts and senior engineers when a problem exceeds current experience.
• Ability to learn when policies and processes are standardized and when they differ across teams, environments, technologies, and operational scenarios.
• Awareness of advancements and changes in data engineering, database technologies, cloud platforms, data models, enterprise information management, business intelligence, and data science.
• Ability to respectfully challenge assumptions, authority, or the status quo when there is a clear technical or operational rationale.

Details

• Location: Gurgaon, India.
• Supported technologies include Elasticsearch, AWS Managed Databases, MongoDB, MySQL, PostgreSQL, Redis, and related cloud database services.