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Tier-1 brand, metro Bangalore, mid-level generalist data engineer with broad Azure skillset increases competition.
Data engineering skills are transferable, but Azure/platform expertise adds moderate industry specificity.
Explicit 4+ years plus mandatory Azure, Python, and pipeline tooling makes shortlisting strict.
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Design, develop, and maintain scalable, modular, and resilient data pipelines in Azure cloud environments to support AI/ML teams and multiple stakeholders.
Implement ETL/ELT workflows for structured, semi-structured, and unstructured data using Azure and cloud-native tools, ensuring performance and low maintenance.
Coordinate with process owners to understand requirements, resolve issues in robotic processes, and establish data validation, logging, monitoring, and compliance with governance policies.
4+ years of experience designing and deploying scalable data pipelines in cloud environments.
Proficiency in Python, SQL, and data manipulation frameworks such as Apache Airflow, Spark, dbt, Pandas.
Experience with Azure Data Factory, AzureML Studio, Azure Storage and handling semi and unstructured data.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Experienced in working with cloud data lakes, warehouses (e.g., Redshift, Snowflake, BigQuery), and streaming platforms (e.g., Kafka, Kinesis).
Able to optimize data infrastructure for scalability, cost-efficiency, and observability in cloud-based environments.
Familiar with CI/CD for data pipelines and infrastructure-as-code tools like Terraform or CloudFormation, with strong data modelling and schema design expertise.