Engineering Manager II, Data

2 weeks ago

Hyderabad, Telangana, India Uber Full time ₹ 15,00,000 - ₹ 60,00,000 per year

About The Role
As an
Engineering Manager on the FinTech Data & ML Systems team
, you will:

  • Lead a high-performing team of data engineers and platform specialists in designing, implementing, and scaling data and ML solutions that power analytics, decision-making, and automation across FinTech.
  • Drive the architecture and delivery of robust data pipelines, feature stores, and data platforms that enable machine learning and advanced analytics use cases.
  • Collaborate closely with product managers, data scientists, and ML engineers to define and deliver reliable data and model workflows that support critical FinTech applications.
  • Provide technical leadership in data architecture, ETL design, model training pipelines, and productionization of ML workflows.
  • Identify opportunities to use data and ML to solve key business challenges, improve efficiency, and unlock new capabilities across payments, compliance, and financial systems.
  • Promote a culture of technical excellence , encouraging best practices in system design, testing, observability, and maintainability across both data and ML domains.
  • Mentor and develop engineers , fostering a collaborative, inclusive, and high-performance culture where teams can experiment, learn, and grow.
  • Ensure reliability and scalability of FinTech data and ML systems through strong engineering discipline and well-defined operational practices.

*Basic Qualifications*

  • Proven experience as a Software or Data Engineering Manager , leading teams that deliver large-scale data infrastructure or platform solutions.
  • Deep technical expertise in distributed data systems , including data ingestion, transformation, storage, and streaming.
  • Working knowledge of machine learning workflows and supporting infrastructure (e.g., feature engineering, model training, deployment, and monitoring).
  • Strong leadership, communication, and cross-functional collaboration skills - especially when partnering with analytics, data science, and product teams.
  • Demonstrated ability to set vision, define roadmaps, and deliver data-driven solutions that support analytics and ML applications.
  • Passion for mentoring engineers and fostering an environment of learning, innovation, and accountability.
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field .

*Preferred Qualifications*

  • Experience designing or supporting data and ML infrastructure , such as feature stores, model registries, or experimentation platforms.
  • Hands-on familiarity with big data and orchestration technologies (e.g., Spark, Airflow, Flink, Kafka, or equivalent).
  • Understanding of ML operations (MLOps) and best practices for operationalizing models at scale.
  • Experience in FinTech or Payments , especially in domains involving risk, fraud, compliance, or automation.
  • Knowledge of data privacy, regulatory , and compliance requirements in financial systems.
  • Advanced degree (Master's or PhD) in Computer Science, Engineering, or a related field .

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