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PwC brand, Bangalore metro, mid-level generalist role, and broad toolset increase competition.
Core big-data and cloud engineering skills are highly transferable across industries.
Explicit 5–8 years plus extensive mandatory tech stack increases shortlisting rigor.
Design and build data infrastructure, including data pipelines, integration, and transformation solutions.
Leverage big data technologies and cloud platforms, primarily AWS and Azure, to enable efficient data processing and analysis.
Apply advanced programming skills in Spark, Python/Scala, and manage tools like Kafka, Airflow, DBT, and Flink for delivering enterprise data solutions.
5-8 years of relevant work experience in data engineering or related fields.
Mandatory skills: Big Data technologies, AWS (including S3, Glue, EMR, Lambda, Kinesis), SQL, Python/Scala, Spark, Aurora PostGres, Kafka, Airflow, DBT, Flink, Apache Iceberg, Datadog.
Education: B.Tech / M.Tech / M.E / MCA / B.E in relevant field.
Experience with CI/CD frameworks and popular code repositories (e.g., GitHub) mandatory.
Experienced in handling complex big data environments with proficiency in both cloud (AWS, Azure) and open source tools.
Capable of end-to-end ownership of data engineering solutions with a strong focus on scalable, maintainable pipelines.
Comfortable working within a technology-driven advisory environment serving enterprise clients requiring robust data and analytics platforms.