Technical Lead

Job Description:

A seasoned technical leader is required to architect, implement and scale our end-to-end data platform built on AWS. You will lead a team of engineers while working cross-functionally with stakeholders from fraud, finance, product and engineering to enable reliable, timely and secure data access across the business.

Responsibilities:

• Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services.
  
• Leading the development of ingestion, transformation and storage pipelines using AWS Glue, DMS, Kinesis/Kafka and PySpark.
  
• Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services.
  
• Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation and reporting use cases.
  
• Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment.
  
• Collaborating with InfoSec, SRE and Data Governance teams to enforce data security, lineage tracking, access control and compliance.
  
• Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds and performance insights.
  
• Mentoring data engineers, setting technical direction and ensuring delivery of high-quality observable data pipelines.
  

Requirements:

• At-least 7 years of experience in data engineering.
  
• Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS and Redshift Spectrum.
  
• Expertise in designing data pipelines for real-time, streaming and batch systems, including schema design, format optimization and SLAs.
  
• Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation.
  
• Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale.
  
• Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions.
  
• Experience implementing data access controls, encryption policies and compliance workflows in regulated environments.
  
• Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains.
  
• Demonstrated ability to lead teams, drive architectural decisions and collaborate with cross-functional stakeholders.
  

Brownie Points:

• Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements.
  
• Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis or fraud detection.
  
• Familiarity with data contracts, data mesh patterns and data as a product principles.
  
• Experience using GenAI to automate data documentation, generate data tests or support reconciliation use cases.
  
• Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena and S3.
  
• Experience building data platforms for ML/AI teams or integrating with model feature stores.
  

Benefits:

• Cultivate a dynamic and innovative culture that fuels growth, creativity and collaboration.
  
• Focus on employee development, supporting continuous learning and growth through training programs, learning on the job and mentorship.
  
• Encourage speaking up, sharing ideas and taking ownership.
  
• Embrace diversity and foster a rich exchange of perspectives and experiences.
  
• Make a meaningful impact on people's lives through fintech and e-commerce.
  

Personal Data Protection Act:

By submitting your application for this job, you are authorizing the company to collect and use your personal data, and to disclose such data to any third party with whom the company has service arrangements, in each case for all purposes in connection with your job application and employment.

The company will retain your personal data for one year for consideration of future job opportunities.

• Mid-Senior level
  

• Full-time