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Mid-level Data Engineer in Bangalore at a well-known global firm with broad skill requirements increases competition.
Core data engineering skills (Python, Spark, SQL, ETL) are highly transferable across industries.
Explicit 4–7 years plus mandatory Spark, Python, SQL, and data architecture requirements increase shortlisting strictness.
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Design, develop, and maintain scalable data pipelines and architectures using Python, SQL, and big data technologies.
Build and optimize data ingestion and transformation scripts integrating data from APIs, third party services, and internal databases.
Collaborate with Data Science, Analytics, QA, and DevOps teams to deliver robust, high performance data solutions supporting business intelligence and strategic objectives.
4-7 years of work experience in data engineering or related roles.
Bachelor's degree in Computer Science or related field.
Proficiency in Python or Scala and advanced SQL with experience in Spark, Hadoop, or similar distributed processing frameworks.
Experience with workflow orchestration tools like Apache Airflow, Prefect, or Dagster and strong understanding of data modeling and data warehousing architectures.
Experienced with building and optimizing large-scale data pipelines and integrations in complex environments involving APIs and multiple data sources.
Strong technical skills in distributed data processing frameworks, data modeling, and orchestration tools indicating senior software engineer level proficiency.
Ability to work cross-functionally with data scientists, analysts, QA, and DevOps teams to deliver end-to-end data engineering solutions aligned with organizational strategic goals.