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Popular mid-level Data Engineer title, metro Pune location, and broad cloud/dbt skillset create strong applicant competition.
Core data engineering skills (dbt, Snowflake, SQL, Python, CI/CD) are broadly transferable across industries.
Explicit 4–6 years plus mandatory dbt, Snowflake, SQL, Python, and CI/CD requirements produce high shortlisting rigidity.
Own end-to-end design, development, testing, deployment, and maintenance of data models and pipelines using dbt on Snowflake, ensuring production-ready, performant, and documented solutions.
Engage with cross-functional business stakeholders (Analytics, Operations, GTM, G&A) to translate problem statements into clear, actionable data requirements.
Manage CI/CD pipelines and scheduling of dbt jobs, ensure pipeline reliability and SLA adherence, and collaborate on AWS resource provisioning for data infrastructure.
4–6 years of experience in data engineering, backend engineering, or similar roles.
Bachelor's degree in Computer Science, Mathematics, Engineering, Statistics, or related field.
Hands-on experience with dbt in a data warehouse environment (preferably Snowflake).
Proficiency with SQL (advanced queries, window functions), Python scripting, AWS core services (S3, Lambda, IAM), and CI/CD pipelines (GitHub Actions preferred).
Experienced in dimensional data modeling balancing clarity, performance, and flexibility, with strong software engineering practices treating data code as maintainable software.
Comfortable working closely with infrastructure and cloud resource provisioning (Terraform experience a plus) and ownership in pipeline scheduling, observability, and deployment.
Able to bridge business and technical teams by translating analytical problem statements into well-structured data solutions and ensuring high data quality and documentation.