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Tier-1 brand, mid-level generalist data role, and metro Hyderabad increase applicant competition.
Core data engineering skills are broadly transferable across industries, reducing background sensitivity.
Explicit 3+ years plus many mandatory tech requirements (Snowflake, dbt, Airflow, Python, CI/CD) increases filter rigidity.
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Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, dbt, and Snowflake for data ingestion and transformation.
Orchestrate and monitor data workflows with Airflow and Snowflake Tasks, implement data quality checks and manage data storage across AWS S3 and Apache Iceberg.
Collaborate with Data Science teams to deliver well-modelled data assets, support data governance, and contribute to CI/CD and infrastructure automation.
Minimum 3 years of experience in data engineering or related roles delivering reliable data pipelines.
Proficiency with Python, SQL, dbt, Snowflake (including DDL and performance tuning), and orchestration tools such as Airflow or Snowflake Tasks.
Experience with cloud storage (AWS S3, Apache Iceberg), Git-based version control, CI/CD pipelines (GitLab CI/CD), and Docker.
Work Experience Required: 3+ years as specified; Location: Hyderabad, India; Work model: Hybrid.
Experienced in building scalable data infrastructure in cloud environments, specifically with Snowflake and modern data workflows.
Familiar with integrating AI/ML infrastructure components such as feature stores, model registries, and vector databases.
Strong operational focus on data quality, governance, automation, and collaboration across data and analytics teams in a global publishing context.