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Mid-level generalist data role in Bangalore at a well-known global firm increases applicant competition.
Core data engineering skills transfer across industries despite domain-specific supply chain preferences.
Explicit 4-year minimum plus many mandatory data engineering technologies required.
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Design, build, and maintain moderately complex data systems, including scalable and robust data products and pipelines for batch and streaming workloads.
Develop, optimize, and support data pipelines and data infrastructure for efficient data ingestion, transformation, storage, and retrieval.
Collaborate with multi-functional teams to gather requirements and implement data governance, automation, and data modeling for improved analytics and data accessibility.
Minimum 4 years of relevant work experience with a Bachelor's degree.
Proficiency with Big Data technologies such as Hadoop ecosystem (HDFS, Hive, MapReduce) and Apache Spark (PySpark, Spark SQL).
Strong skills in Python, Scala (for Spark), and advanced SQL for large-scale analytical queries.
Experience designing and maintaining ETL/ELT pipelines using Spark Structured Streaming, Kafka Connect, Airflow/Azure Data Factory or Glue, including automated deployments and data governance.
Experience with cloud data warehouses like Snowflake and Lakehouse Architecture and transactional data system management (backup/restore, replication, high availability).
Familiarity with data governance frameworks including data quality, metadata management, security compliance (PII masking, role-based access).
Has exposure to real-time streaming platforms (e.g., Apache Kafka), CI/CD pipelines, containerization (Docker) and Kubernetes for data workflow orchestration.