Lead Data Support Engineer

3 weeks ago

Hyderabad, India Inspire Brands Hyderabad Support Center Full time

About Inspire:

Inspire Brands is a multi-brand restaurant company whose current portfolio includes nearly 32,000 Arbys, Baskin-Robbins, Buffalo Wild Wings, Dunkin, Jimmy Johns, and SONIC Drive-In locations worldwide. The company was founded in 2018 and is headquartered in Atlanta, Georgia.

About Inspire Brands Hyderabad Support Center:

Inspire fosters a culture of innovation that encourages team members to take risks, test, and learn. We want to create an environment where ideas emerge and succeed at every level.

Inspire Brands is disrupting the restaurant industry through digital transformation across multiple brands. The companys technology hub, Inspire Brands Hyderabad Support Center, will lead technology innovation and product development for the organization and its portfolio of distinct brands (both current and future). The Center will focus on developing new capabilities in data science, data analytics, eCommerce, automation, cloud computing, and information security to accelerate the companys rapid growth and influence how we reach the guest and, more importantly, how the guest wants to interface with us.

Inspires Hyderabad Support Center will also host an innovation lab and collaborate with start-ups to develop solutions for productivity optimization, workforce management, loyalty management, payments systems, and more.

Job Description:

We are seeking a skilled and motivated Data Engineering Support Analyst to join our team. As a Data Engineering Support Analyst, you will play a crucial role in ensuring the smooth operation and support of our data engineering. Your primary responsibility will be to provide monitoring, and technical assistance, troubleshoot issues, and maintain the reliability and efficiency of our data systems.

Responsibilities:

  • Provide L1/L2/L3 support and maintenance for the data engineering platform.
  • Monitor Jobs, troubleshoot failures, and provide the fix to failed jobs.
  • Ensure data availability SLA is met.
  • Resolve data quality issues by reloading the data into production environments.
  • proactively identify areas for improvement.
  • Perform Root Cause Analysis (RCA) of the identified issue.
  • Collaborate with data engineers and other teams to diagnose and resolve technical issues.
  • Troubleshoot data-related problems, including data quality issues and job failures.
  • Implement and maintain data pipelines, ensuring their reliability and efficiency.
  • Assist in the development and optimization of data processing workflows.
  • Document processes, procedures, and troubleshooting steps for reference and training purposes.
  • Collaborate with cross-functional teams to ensure data infrastructure meets business needs.
  • Stay updated with industry trends and best practices in data engineering and support.

Requirements:

Bachelor's degree in Computer Science, Information Technology, or a related field.

  • Experience of 6-8 years in delivering operational support for Data Platforms.
  • Proven experience in data engineering, data analysis, or a similar role.
  • Strong knowledge of Snowflake.
  • Proficiency in scripting or programming languages (Scala, Pi-spark).
  • Strong knowledge of Airflow orchestration
  • Experience with data pipeline tools (Azure Data Factory, Databricks, SNOWSQL)
  • Knowledge of JIRA, Confluence, ServiceNow (or any other ITSM tool)
  • Strong knowledge of Azure DevOps (CI/CD pipelines)
  • Familiarity with data warehousing concepts and technologies.
  • Excellent problem-solving skills and attention to detail.
  • Ability to work independently and collaborate effectively in a team environment.
  • Ability to lead a team of 8-10 members.
  • Guide and groom the junior team member.
  • Strong communication skills to convey technical concepts to non-technical stakeholders.
  • Flexible availability for weekend and public holiday coverage on a rotational schedule.
  • Adaptability and willingness to learn new technologies and methodologies.

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