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Popular mid-level data role, broad skill requirements, and metro-local demand create high competition.
Data engineering skills are moderately transferable across industries but require specific platform expertise.
Explicit minimum experience plus many mandatory big-data and cloud skills enforce strict screening.
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Design, build, and maintain scalable ETL/ELT data pipelines across cloud and big data ecosystems.
Work with distributed systems such as Hadoop and Apache Spark; optimize data warehouses in Snowflake.
Implement data modeling, manage complex workflows using Apache Airflow, and ensure data quality and performance optimization.
2+ years of experience in data engineering or related roles.
Proficiency in Python, PySpark, Advanced SQL, shell scripting, and experience with cloud platforms (AWS, Azure, or GCP).
Experience with Hadoop, Apache Spark, Snowflake, Apache Airflow, version control using Git, and CI/CD frameworks.
Work Experience Required: 2+ years; Location: Indore.
Experienced with large-scale distributed data systems and scalable cloud data architecture.
Skilled in managing both structured and semi-structured data formats and optimizing data workflows.
Capable of independently handling complex data pipelines and maintaining data quality with strong technical expertise.