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High: mid-level generalist data role in Bengaluru with broad tech stack and recognizable corporate brand.
Low: core data engineering skills like Spark, Kafka, Databricks, and AWS transfer easily across industries.
High: explicit 4+ years plus multiple mandatory platform, streaming, and cloud technology requirements.
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Design and develop scalable data ingestion, transformation, and processing frameworks using Databricks, Spark, Kafka, Airflow, DBT, and cloud-native services.
Build and optimize data models, lakehouse architectures, and data products supporting analytics, reporting, machine learning, and operational needs.
Collaborate with product managers, analysts, data scientists, and engineers to translate business requirements into data solutions, ensuring security and governance compliance.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
At least 4+ years of experience building large-scale data engineering solutions and platforms.
Hands-on expertise with Databricks, Snowflake, Python, PySpark, SQL, Apache Spark or Flink, Kafka, Airflow, and AWS cloud services (S3, Lambda, Glue, DynamoDB, Redshift, EMR).
Experience with batch and streaming data pipelines, dimensional modeling, data warehousing, and lakehouse architectures.
Experienced in designing scalable, resilient, and observable data systems focused on reliability and maintainability.
Proven track record of delivering end-to-end data solutions from concept to production with ownership of operational support.
Strong problem-solving skills optimizing performance at scale and enabling advanced analytics, machine learning, or AI-driven applications.