- Architect and build scalable, high-performance data pipelines and infrastructure.

- Provide technical leadership across complex, cross-functional data initiatives.

- Guide and mentor a team of data engineers, ensuring best practices and high engineering standards.

- Collaborate with data scientists, analysts, and product teams to understand data needs and implement efficient data solutions.

- Define data modeling standards and optimize performance across diverse data workloads.

- Lead design and implementation of real-time and batch data processing architectures.

- Own and drive infrastructure-as-code and DevOps integration for data platform deployments.

Key Skills & Expertise :

Cloud & Infrastructure :

- Deep hands-on expertise with AWS (S3, Redshift, Lambda, Glue, etc.)

- Advanced experience with Snowflake data warehouse

- Proficient in Terraform / CloudFormation for infrastructure as code

- Strong understanding of CI/CD pipelines using Jenkins, Bitbucket, or similar tools

Programming & Scripting :

- Expert-level proficiency in Python and PySpark for large-scale data transformations

- Advanced SQL for complex querying, performance tuning, and data modeling

ETL & Data Architecture :

- Proven experience in designing event-driven architectures and real-time data ingestion

- Hands-on with API-based ingestion, data validation frameworks, archival strategies, and incremental loading

- Strong understanding of data governance, security, and compliance in a cloud environment

Preferred Qualifications :

- Bachelors/Masters degree in Computer Science, Engineering, or a related field

- Experience with streaming platforms like Kafka, Kinesis, or Spark Streaming

- Familiarity with data lake and data mesh architectures is a plus

- Excellent communication, leadership, and stakeholder management skills