Support Engineer - 2

Effectively triage and manage support tickets, ensuring proper categorization, documentation, and tracking of reported issues.

Proficiency in Cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) is vital. This knowledge enables support personnel to understand and troubleshoot data pipeline issues.

Understanding data ingestion and Extraction, Transformation, and Loading (ETL) processes is crucial for resolving issues related to data pipeline activities.

A strong understanding of Databricks and Apache Spark is preferred for troubleshooting data pipeline issues. This includes knowledge of Spark job execution, data ingestion, transformations, and optimizations.

Proficiency in SQL is important for querying and manipulating data within Databricks. Additionally, knowledge of programming languages like Python or Scala enables support personnel to analyse and debug code related to data pipeline activities.

The support personnel should be well-versed with data visualization and reporting concepts. This allows them to assist end users with actual issues on visualization and data components.

The candidate needs to have in-depth knowledge of the platform infrastructure, including server architecture, networking, security protocols, API details, process flow and scalability. This enables them to troubleshoot issues related to the platforms performance and ensure its stability.

L1 and L2 support require individuals who can quickly analyse complex issues, break them down into manageable components, and propose effective solutions.

They should possess excellent problem-solving and analytical skills to address data and platform-related challenges.

Clear and concise communication is crucial for L1 and L2 support roles. The support personnel must be able to understand user queries and relay technical information effectively, whether its providing step-by-step guidance or documenting issues and resolutions.

Offer comprehensive user guidance and assistance, ensuring users can navigate the UI product and maximize its features.

Collaborate with internal teams to escalate complex issues, communicate bug reports, usability concerns, and contribute to feature enhancement discussions.

Conduct deep analysis and troubleshooting for L2 support, investigating complex UI-related problems, analysing logs, and performing root cause analysis.

Familiarity with incident management tools like Jira, Zendesk, or ServiceNow is beneficial. Understanding the incident management process ensures proper tracking, prioritization, and resolution of support tickets related to data and platform features.

Bachelor s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science.

Hands-on Support engineer who is curious about technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure(preferred), etc.), Data concepts, Data debugging and understanding, Micro Services, UI features, Data Security, etc.

4+ years of experience as a data developer/Support Engineering on Python-spark, Azure SQL Server, Cosmos DB/Mongo DB

Hands-on Experience of building/maintaining Data Pipelines on Cloud and well versed with CICD/DevOps process.

Strong coding skills in languages like Python, SQL, or Scala are essential for understanding, troubleshooting and fixing data and platform features.

Strong understanding of UI product features, functionality, and user experience.

Proficient understanding of JavaScript and React JS, including the ability to identify and debug issues using logs and provide detailed information.

Strong attention to detail, organizational skills, and the ability to prioritize tasks effectively.

Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams