11 hours ago
Remote, India or Bengaluru, IndiaSenior
Responsibilities
- Design, develop, and implement scalable batch and real-time data pipelines using Snowflake, Amazon Redshift, and AWS-native technologies.
- Lead end-to-end data engineering initiatives covering ingestion, transformation, data quality, and data delivery.
- Build and optimize cloud-native data solutions using AWS services including S3, Lambda, Glue, ECS, EMR, IAM, and CloudWatch.
- Develop and maintain modular, testable, and scalable data models and transformations with dbt.
- Gather requirements and translate business needs into technical solutions with cross-functional stakeholders.
- Drive data modeling, governance, metadata management, lineage, and performance optimization practices.
- Implement observability and monitoring solutions using Datadog, CloudWatch, and custom alerting frameworks.
- Lead code reviews, establish engineering standards, and champion CI/CD and DevOps practices for data platforms.
- Troubleshoot complex production issues involving data pipelines, orchestration, and warehouse performance.
- Mentor junior and mid-level engineers and lead technical initiatives.
- Build trusted datasets that support advanced analytics and GenAI applications.
- Deliver secure, compliant, and highly available enterprise data solutions.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
- At least 5 years of experience in data engineering, data warehousing, and software development.
- Strong SQL and Python skills with experience building enterprise-scale data solutions.
- Hands-on production experience with Snowflake and Amazon Redshift.
- Strong experience with dbt or comparable modern data transformation frameworks.
- Experience with orchestration and workflow tools such as Apache Airflow.
- Experience building and supporting observability frameworks using Datadog or equivalent monitoring platforms.
- Strong understanding of dimensional and normalized data modeling.
- Experience with AWS services including S3, Lambda, Glue, IAM, ECS, and CloudFormation.
- Knowledge of CI/CD implementation using GitHub Actions, Jenkins, Terraform, or similar platforms.
- Experience with data governance, data quality frameworks, and security best practices.
- Excellent problem-solving, analytical, and communication skills.
- Proven ability to lead technical initiatives and mentor engineering teams.
- Passion for innovation, continuous learning, and modern data engineering practices.
Benefits
- Flexible work environment and fluid career paths.
- Internal mobility opportunities and support for career growth.
- Emphasis on purpose, well-being, work-life balance, and an inclusive workplace.
- Volunteer opportunities supporting community causes.
Tech Stack
Categories
Data Engineering
