Job responsibilities
- Provides guidance to immediate team of software engineers on daily tasks and activities
- Sets the overall guidance and expectations for team output, practices, and collaboration
- Anticipates dependencies with other teams to deliver products and applications in line with business requirements
- Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirements
- Creates a culture of diversity, equity, inclusion, and respect for the team members and prioritizes diverse representation
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience.
- Experience leading technology projects and Experience managing technologists.
- Minimum 8 yrs proven experience in full-stack software development, using Java, Spring based technologies in AWS / Cloud environment.
- Demonstrable success in leading and managing software engineering teams, with a focus on individual growth and overall team performance.
- Proven experience with Apache Spark (batch and streaming) for large-scale data processing.
- Proven experience and strong knowledge of AWS services including S3, EC2, EMR, ECS, Lambda, Glue, Aurora DB, SQS , SNS, Step function, API Gateway.
- Expertise in Databricks and Snowflake for collaborative data engineering and analytics.
- Experience in Apace Iceberg for large scale analytics on Data lake.
- Experience with Terraform for provisioning, securing, and managing cloud infrastructure for data workloads.
- Good knowledge of data governance, access controls, data lineage, and compliance standards for implementing secure data pipelines and handling sensitive information responsibly.
- Proficiency in tuning Spark jobs, optimizing SQL queries on Snowflake, and troubleshooting distributed systems.
Preferred qualifications, capabilities, and skills
- Experience with CI/CD pipelines for automated deployment. Implementing automated testing strategies including Unit , Contract, integrations, and end to end tests.
- Knowledge in building scalable RESTful APIs using Spring Boot .
- Experience with PySpark for developing Spark-based data pipelines using Python.
- Experience integrating AI agents or automation frameworks to optimize data engineering tasks.