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Mid-level data-engineer in Mumbai with broad cloud/Databricks skills and known consulting brand drives high competition.
Technical data-engineering skills are transferable, but Databricks/AWS and regulated-consulting experience raise domain specificity.
Multiple mandatory technical skills (Databricks, Spark, AWS, dbt, Airflow) and 5+ years experience enforce high strictness.
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Design, build, and operate scalable, cloud-native data platforms and production-grade batch and streaming data pipelines using AWS, Databricks, and Apache Spark.
Develop and maintain high-throughput, low-latency data processing systems; ensure solutions are secure, tested, observable, and cost-efficient for live enterprise environments handling 10s to 100s TB of data.
Collaborate with business and technology stakeholders, supporting production systems through troubleshooting, continuous improvements, and enforcing data quality, modelling, security, and governance.
5+ years of hands-on data engineering experience in production environments.
Strong proficiency in Python, Java (or similar), SQL; experience with Databricks, Apache Spark, AWS, dbt, and Airflow (or equivalent orchestration tool).
Experience building and operating batch and streaming data pipelines at enterprise scale (handling large data volumes).
Experience with relational databases (Postgres or SQL Server), CI/CD pipelines, testing frameworks, and monitoring/observability tools.
Has demonstrated ownership and hands-on involvement across the full data pipeline lifecycle including design, implementation, security, governance, deployment, and production support.
Comfortable working with multiple stakeholders including business analysts, architects, data scientists, and end users in complex enterprise environments.
Able to explain technical decisions and trade-offs clearly, with practical experience influencing design and technical strategy in large-scale data engineering projects.