Associate Distinguished Engineer - Lead Data Engineer

Atlanta, Georgia, United States

Nagarro

A digital product engineering leader, Nagarro drives technology-led business breakthroughs for industry leaders and challengers through agility and innovation.

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Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (19000+ experts across 34 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

Your role will actively lead the Data Operations Team, in maintaining & operating the data platform capabilities & ensuring smooth and efficient operations. We are looking for a candidate who has an inclination for cost optimizations, process automations & improvements, Study the system to identify gaps & close. Identifying & Monitoring major Operational KPIs; Assess current operational maturity and advancing to the next level.

Job Responsibilities:

  • You will play a critical role in ensuring the smooth and efficient operations of data management and analytics processes within the organization, overseeing data operations, implementing frameworks & standards, and providing continuous improvement in data related workflows. 
  • Oversee the day-to-day operations including monitoring, data ingestion, regular checks for issues, anomalies, and bottlenecks & issue resolution.
  • Support the team to take the capabilities of the platforms and put them into an operational practice.
  • Collaborate with cross-functional teams, including data engineers, data scientists, business analysts, and IT teams, to understand data requirements and ensure data operations meet business needs.
  • Collaborate with the data engineering team to optimize data workflows and ensure efficient data operations.
  • Implement monitoring systems and processes to track the performance and observability of data.
  • Lead data incident management processes, including data outages, breaches, or data related disruptions.
  • Evaluate, select, and implement data management tools and infrastructure that support efficient data operations if need be.
  • Create and maintain comprehensive documentation (Runbooks), including data operation processes, standard operating procedures, and best practices.
  • Mentor team members.
  • Stay up to date with emerging cloud technologies and best practices in data management and operations to enhance data capabilities. 
  • Ensure Accountability, Adherence to process/SoP's, standards and communication.
  • Delivery (quality, on-time & velocity), Ensure Ingestion deployments without any bugs/issues. • Keeping runbooks updated | Standardizing documentation & continuous updates it every month. •  
  • Perform quality controls and monitor production Key Performance Indicators (KPIs) to ensure consistent, high-quality output.

Qualifications

  • 15+ years of experience in Data and Analytics
  • 5+ years of experience in leading Data Engg Operations Teams
  • Team leadership experience
  • Extensive experience in data engineering operations, data management, or related roles
  • Experience with data monitoring and performance optimization techniques.
  • Good knowledge of cloud platforms, AWS and related services for data storage, data processing, and infrastructure provisioning

Additional Information

Disclaimer: Nagarro is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will be afforded equal employment opportunities without discrimination based on race, creed, color, national origin, sex, age, disability, or marital status.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: AWS Data management DataOps Engineering KPIs

Region: North America
Country: United States
Job stats:  4  2  0

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