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Mid-level, Hyderabad data engineer role with common Airflow/Snowflake skills creates moderate competition.
Data engineering skills like Python, Airflow, SQL and cloud are highly transferable across industries.
Explicit 2–4 years, Airflow plus Python, cloud and SQL requirements increase shortlisting strictness.
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Develop and maintain scalable data pipelines and ETL/ELT workflows using Python, Apache Airflow, and cloud data platforms like AWS and Snowflake.
Build and automate data ingestion, transformation, scheduling workflows including custom Airflow DAGs with operators, sensors, and hooks.
Monitor and troubleshoot data pipelines to ensure high availability and optimize performance of SQL queries and data transformations.
2 to 4 years of Python development experience with advanced scripting and automation.
1+ years of experience with Apache Airflow including DAG design, orchestration, and scheduling.
Experience with AWS services such as S3, Glue, Lambda, Athena or equivalent cloud technologies.
Strong hands-on skills in SQL including advanced querying and query optimization.
Experienced in building and managing production data pipelines in cloud environments, specifically with Apache Airflow and AWS/Snowflake.
Proficient in designing custom Airflow DAGs and handling complex ETL/ELT workflows with a focus on automation and reliability.
Capable of collaborating with cross-functional teams to understand requirements and deliver scalable and maintainable data engineering solutions.